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1.
2014年3月13日至4月20日在福建三明市利用PM2.5中流量采样器采集大气中PM2.5膜样品,测定了PM2.5的质量浓度,并用热/光碳分析仪和离子色谱分析了其组分变化特征.结果表明,三明市观测期间PM2.5的平均质量浓度为73.61±0.73 μg/m3,有机碳(OC)和元素碳(EC)的平均质量浓度分别为7.26±1.00和5.63±0.27 μg/m3,水溶性离子中SO42-、NH4+、NO3-和Na+的质量浓度分别为18.08±12.19、4.18±3.56、2.77±1.16和2.73±0.23 μg/m3,总和占总水溶性离子的87.76%.结合后向轨迹分析了福建三明市的污染物来源特征.该地区OC/EC的平均比值小于2,SOC(二次有机碳)生成量很少,主要以一次有机污染物为主,OC、EC与K+的相关性分析表明OC、EC与K+的来源相近,可以判断OC、EC绝大部分来源是生物质燃烧产生的污染物.在水溶性离子分析中,观测期间NO3-/SO42-为0.159±0.02,表明三明市主要以固定源为主,机动车辆等移动源贡献较少.  相似文献   

2.
南京北郊2011年春季气溶胶粒子的散射特征   总被引:3,自引:2,他引:1       下载免费PDF全文
利用南京北郊2011年春季积分浊度仪的观测资料,结合PM2.5质量浓度、能见度和常规气象资料,分析了南京北郊春季气溶胶散射系数的变化特征、散射系数与PM2.5质量浓度和能见度的关系。结果表明,观测期间气溶胶散射系数平均值为311.5±173.3 Mm-1,小时平均值出现频率最高的区间为100~200 Mm-1;散射系数的日变化特征明显,总体为早晚大,中午及午后小。散射系数与PM2.5质量浓度的变化趋势基本一致,但与能见度呈负相关关系。霾天气期间散射系数日平均值为700.5±341.4 Mm-1,最高值达到近1 900 Mm-1;结合地面观测资料、NCEP/NCAR再分析资料和后向轨迹模式分析显示,霾期间气块主要来自南京南部和东南方向。  相似文献   

3.
南京市城市不同功能区PM10和PM2.1质量浓度的季节变化特征   总被引:1,自引:0,他引:1  
使用Anderson-Ⅱ型9级撞击采样器测量了南京市鼓楼商业区、江北工业区、钟山风景区和宁六高速公路交通源春、夏、秋三季的大气气溶胶质量浓度。分析结果表明:南京市PM2.1和PM10的质量浓度存在明显的季节变化,秋季>春季>夏季;ρPM10春季为167.47 μg/m3,夏季为 85.99 μg/m3,秋季为238.99 μg/m3;ρPM2.1春季为59.66 μg/m3,夏季为42.80 μg/m3,秋季为100.15 μg/m3。不同季节中ρPM10ρPM2.1均存在较好的相关性,夏季相关性最好,相关系数为0.952;秋季次之,相关系数为0.783;春季相对较差,相关系数为0.613。城市不同功能区之间ρPM2.1ρPM10的质量浓度值差异很大,交通源>工业区>商业区>风景区。城市不同功能区的质量浓度谱分布基本一致,均为双峰型分布,峰值分别位于0.43~0.65 μm/m3和9.0~10.0 μm/m3。南京市春、夏、秋三个季节大气粒子质量浓度谱为双峰分布,粒子主要集中在0.43~3.3 μm/m3的粒径段。江北工业区ρPM10ρPM2.1质量浓度的相关系数为0.814,略高于鼓楼商业区的0.797。  相似文献   

4.
使用Anderson-Ⅱ型9级撞击采样器测量了南京市鼓楼商业区、江北工业区、钟山风景区和宁六高速公路交通源春、夏、秋三季的大气气溶胶质量浓度。分析结果表明:南京市PM2.1和PM10的质量浓度存在明显的季节变化,秋季>春季>夏季;ρPM10春季为167.47 μg/m3,夏季为 85.99 μg/m3,秋季为238.99 μg/m3;ρPM2.1春季为59.66 μg/m3,夏季为42.80 μg/m3,秋季为100.15 μg/m3。不同季节中ρPM10ρPM2.1均存在较好的相关性,夏季相关性最好,相关系数为0.952;秋季次之,相关系数为0.783;春季相对较差,相关系数为0.613。城市不同功能区之间ρPM2.1ρPM10的质量浓度值差异很大,交通源>工业区>商业区>风景区。城市不同功能区的质量浓度谱分布基本一致,均为双峰型分布,峰值分别位于0.43~0.65 μm/m3和9.0~10.0 μm/m3。南京市春、夏、秋三个季节大气粒子质量浓度谱为双峰分布,粒子主要集中在0.43~3.3 μm/m3的粒径段。江北工业区ρPM10ρPM2.1质量浓度的相关系数为0.814,略高于鼓楼商业区的0.797。  相似文献   

5.
为了监测北京奥运主场馆附近大气颗粒物的污染状况以及评估奥运污染源减排措施对北京大气颗粒物质量浓度变化的影响,利用颗粒物在线监测仪器TEOM于2007年和2008年夏季,在奥运主场馆附近的中国科学院遥感应用研究所办公楼楼顶对大气颗粒物PM10和PM2.5进行了连续同步观测。结果表明,2007年夏季监测点附近大气PM10与PM2.5质量浓度的平均值分别为153.9和71.2μg·m-3,而2008年夏季PM10与PM2.5质量浓度的平均值分别为85.2和52.8μg·m-3。与奥运前一年同时段相比,奥运时段大气PM10和PM2.5的质量浓度分别下降44.5%和25.1%。对比分析奥运前后的2次典型污染过程发现,空气相对湿度的增加和偏南气流输送的共同影响易造成大气颗粒物的累积增长,而降雨的湿清除作用和偏北气流则会使大气颗粒物浓度迅速降低。在相近的气象条件下,奥运前后的污染过程中,大气细粒子的日均增长速率分别为25.1和13.9μg·m-3·d-1,而大气粗粒子的日均增长速率分别为20.8和2.2μg·m-3·d-1,奥运时段污染累积过程中大气粗、细粒子的增长速率分别显著低于和略低于奥运前同时段污染过程中颗粒物的增长速率。污染源减排措施的实施是奥运期间大气颗粒物质量浓度降低的主要原因,从控制效果来看,奥运期间实施的污染源减排措施对大气粗粒子的控制效果明显好于大气细粒子。  相似文献   

6.
基于2016年11月24日—12月23日南京市草场门站、鼓楼站和仙林站的强化试验观测资料,分析了城市和郊区主要大气污染物的时空变化特征及其与气象要素的相互关系。研究发现:观测期间南京PM2.5、PM10、NO2、O3、CO、SO2月均质量浓度分别为52.84~84.34 μg·m-3、88.36~120.34 μg·m-3、49.98~51.66 μg·m-3、24.85~50.57 μg·m-3、0.99~1.2 mg·m-3和22.1~26.48 μg·m-3;近地面,城市大气污染物质量浓度高于郊区,其中城市O3比郊区高61.0%;在城市地区,除NO2和CO外,鼓楼站大气污染物质量浓度高于草场门站,其中鼓楼站PM2.5比草场门站高42.7%;PM2.5小时质量浓度最大为210.93 μg·m-3,重污染过程出现时风速较低、温度较高,郊区PM10、PM2.5、NO2质量浓度呈现高值时的最频风向为南风,O3和SO2质量浓度呈现高值时的最频风向分别为西风和西南风,所以郊区大气污染受城市输送影响。利用HYSPLIT模式研究发现12月4—8日和16—20日的污染气团分别来自西部和北方地区,聚类分析发现12月影响南京市的污染气团45%来自西部地区且移动速度较快,55%来自北方地区且移动速度较慢。由此可见,南京市冬季出现的大气污染,其形成不仅与本地排放和局地气象条件有关,而且西部和北方地区的远距离输送也会造成影响。  相似文献   

7.
针对地面站点稀疏不足以提供高空间覆盖、高空间分辨率的面域PM2.5数据支撑区域细颗粒物污染防治的问题,以湖北地区2015-2017年的MODIS卫星遥感气溶胶光学厚度(AOD)产品数据为主预测量,结合温度、湿度、风速、压强等气象参数和植被指数数据等辅助预测量,建立了AOD-PM2.5关系逐日变化的线性混合效应(LME)模型,用于估算湖北地区的PM2.5浓度水平.利用十折交叉验证方法进行了模型精度评估.结果表明:1)2015-2017年的交叉验证R2分别达到0.89、0.85和0.88,利用MODIS AOD数据反演近地面PM2.5质量浓度的线性混合效应模型能很好地用于区域细颗粒物遥感监测;2)省内PM2.5质量浓度空间差异显著,鄂东、鄂南和鄂北高,鄂西北和鄂东南低;3)全省PM2.5估算时空数据年均值呈下降态势,分别为65.6±39.8、57.1±34.1和48.1±28.3 μg/m3,各市除随州、咸宁2016、2017年年均值持平外,都呈下降趋势.  相似文献   

8.
对2017年11月1日—2018年1月31日与2018年11月1日—2019年1月31日连续两年青岛市大气PM1进行监测,获取了PM1中含碳组分的变化趋势,结合国控站点监测数据和气象条件,分析了秋冬季PM1来源.结果表明:2017、2018年秋冬季观测期间PM1日均质量浓度分别为40.58±25.98、42.55±25.05 μg/m3;霾日质量浓度分别为84.71±16.70、81.52±18.39 μg/m3.与2017年相比,2018年同期PM1质量浓度增长4.85%,霾日下降3.76%.2017年霾日PM1中OC、EC质量浓度分别为13.67±3.95、3.95±1.02 μg/m3,2018年分别为16.48±6.34、3.34±1.16 μg/m3.与2017年相比,2018年霾日OC质量浓度增长20.56%,EC下降15.44%.2017、2018年霾日SOC质量浓度分别是非霾日的1.28和2.15倍,表明霾污染发生时易发生有机碳二次转化.含碳组分主成分分析均解析出3个因子.因子1解释变量均最大,分别为58.98%、67.14%,其表征含碳组分主要源于生物质燃烧、燃煤、道路扬尘及汽油车尾气等排放源.由后向气流轨迹分析得出,2017、2018年秋冬季气团轨迹多起源于内蒙古,经河北、天津、山东等省市抵达青岛.  相似文献   

9.
冬季南京北郊大气气溶胶中水溶性阴离子特征   总被引:3,自引:2,他引:1       下载免费PDF全文
2009年冬季在南京北郊进行24 h采样,运用离子色谱法研究大气PM10中水溶性阴离子的分布特征。结果表明:PM10中阴离子的平均总质量浓度在白天和夜间分别为658.21、622.84 μg/m3;PM2.1则分别为337.86、319.97 μg/m3,阴离子主要存在于细粒子中;主要水溶性阴离子均为SO42-,且海盐对南京北郊大气PM10和PM2.1中的SO42-质量浓度影响很小。SO42-、Cl-和F-粒径谱分布相似,均呈双模态;NO3-和NO2-主要呈现单模态。SO42-与NO3-、F-与NO3-、SO42-与Cl-的相关系数均大于0.8,相关显著,说明其存在一定的同源性。NO3-/SO42-的平均值在白天、夜间分别为0.058 2、0.048 4,说明南京北郊大气污染以固定源为主。分析NO3-、SO42-前体物的转化率知道,采样期间SOR和NOR的平均值均大于10%,即SO42-部分来源于SO2的二次转化,而不是单一来源于一次污染物。  相似文献   

10.
自2014年以来,中国细颗粒物(PM2.5)浓度大幅度下降,但臭氧(O3)浓度逐年缓慢上升,厘清PM2.5和O3(P-O)相关性尤为关键.在本研究中,2014—2019年北京和南京PM2.5年均质量浓度下降幅度分别为-6.86和-6.15 μg·m-3·a-1;而日最大8小时平均O3质量浓度(MDA8 O3)年均增长幅度为1.50和1.75 μg·m-3·a-1.研究期间,北京地区MDA8 O3质量浓度小于100 μg·m-3,P-O呈负相关;而当质量浓度大于100 μg·m-3时,P-O为正相关.通过Pearson相关系数研究P-O两者相关性.在两个城市每月相关性分析中,在每日时间尺度5—9月为强的正相关;而小时时间尺度11月至次年2月趋于负相关.在北京,P-O每月和季节相关性变化大于南京.在日变化中,夏季在16时为强的正相关,春秋两季在13—17时为弱的正相关,而在春、秋和冬季8时,却为强的负相关.  相似文献   

11.
Results are presented of monitoring measurements of the mass concentration of PM10 (particles with the size of less than 10 μm) and PM2.5 (less than 2.5 μm) fine-dispersed aerosol fractions at the Sainshand and Zamyn-Üüd stations located in the Gobi Desert of Mongolia. Revealed are the annual variations of the mass concentration of PM10 and PM2.5 fine-dispersed aerosol fractions at these stations in 2008. The maximum values of monthly mean concentration during the year were observed in May in the period of dust storms. On the days with the steady calm weather, the mass concentrations of PM10 and PM2.5 varied within 5–8 μg/m3 (PM10) and 3–5 μg/m3 (PM2.5) at the Sainshand station. During the dust storms, the maximum values of concentration exceeded 1400 μg/m3 (PM10) and 380 μg/m3 (PM2.5) that is by 28 (PM10) and 15 (PM2.5) times higher than the maximum permissible concentration for the European Union. Results are given of studying the frequency and duration of dust storms in recent 20 years (1991–2010) in the Eastern Gobi Desert.  相似文献   

12.
This study elucidates the characteristics of ambient PM2.5 (fine) and PM1 (submicron) samples collected between July 2009 and June 2010 in Raipur, India, in terms of water soluble ions, i.e. Na+, NH 4 + , K+, Mg2+, Ca2+, Cl?, NO 3 ? and SO 4 2? . The total number of PM2.5 and PM1 samples collected with eight stage cascade impactor was 120. Annual mean concentrations of PM2.5 and PM1 were 150.9?±?78.6 μg/m3 and 72.5?±?39.0 μg/m3, respectively. The higher particulate matter (PM) mass concentrations during the winter season are essentially due to the increase of biomass burning and temperature inversion. Out of above 8 ions, the most abundant ions were SO 4 2? , NO 3 ? and NH 4 + for both PM2.5 and PM1 aerosols; their average concentrations were 7.86?±?5.86 μg/m3, 3.12?±?2.63 μg/m3 and 1.94?±?1.28 μg/m3 for PM2.5, and 5.61?±?3.79 μg/m3, 1.81?±?1.21 μg/m3 and 1.26?±?0.88 μg/m3 for PM1, respectively. The major secondary species SO 4 2? , NO 3 ? and NH 4 + accounted for 5.81%, 1.88% and 1.40% of the total mass of PM2.5 and 11.10%, 2.68%, and 2.48% of the total mass of PM1, respectively. The source identification was conducted for the ionic species in PM2.5 and PM1 aerosols. The results are discussed by the way of correlations and principal component analysis. Spearman correlation indicated that Cl? and K+ in PM2.5 and PM1 can be originated from similar type of sources. Principal component analysis reveals that there are two major sources (anthropogenic and natural such as soil derived particles) for PM2.5 and PM1 fractions.  相似文献   

13.
Continuous observations of mass concentration and elemental composition of aerosol particles (PM2.5) were conducted at Tongyu, a semi-arid site in Northeast China in the spring of 2006. The average mass concentration of PM2.5 at Tongyu station was 260.9±274.4 μg m^-3 during the observation period. Nine dust events were monitored with a mean concentration of 528.0±302.7 μgm^-3. The PM2.5 level during non- dust storm (NDS) period was 111.65±63.37 μg m^-3. High mass concentration shows that fine-size particles pollution was very serious in the semi-arid area in Northeast China. The enrichment factor values for crust elements during the dust storm (DS) period are close to those in the NDS period, while the enrichment factor values for pollution elements during the NDS period are much higher than those in the DS period, showing these elements were from anthropogenic sources. The ratios of dust elements to Fe were relative constant during the DS period. The Ca/Fe ratio in dust aerosols at Tongyu is remarkably different from that observed in other source regions and downwind regions. Meteorological analysis shows that dust events at Tongyu are usually associated with dry, low pressure and high wind speed weather conditions. Air mass back-trajectory analysis identified three kinds of general pathways were associated with the aerosol particle transport to Tongyu, and the northwest direction pathway was the main transport route.  相似文献   

14.

This study presents the chemical composition (carbonaceous and nitrogenous components) of aerosols (PM2.5 and PM10) along with stable isotopic composition (δ13C and δ15N) collected during winter and the summer months of 2015–16 to explore the possible sources of aerosols in megacity Delhi, India. The mean concentrations (mean?±?standard deviation at 1σ) of PM2.5 and PM10 were 223?±?69 µg m?3 and 328?±?65 µg m?3, respectively during winter season whereas the mean concentrations of PM2.5 and PM10 were 147?±?22 µg m?3 and 236?±?61 µg m?3, respectively during summer season. The mean value of δ13C (range: ??26.4 to ??23.4‰) and δ15N (range: 3.3 to 14.4‰) of PM2.5 were ??25.3?±?0.5‰ and 8.9?±?2.1‰, respectively during winter season whereas the mean value of δ13C (range: ??26.7 to ??25.3‰) and δ15N (range: 2.8 to 11.5‰) of PM2.5 were ??26.1?±?0.4‰ and 6.4?±?2.5‰, respectively during the summer season. Comparison of stable C and N isotopic fingerprints of major identical sources suggested that major portion of PM2.5 and PM10 at Delhi were mainly from fossil fuel combustion (FFC), biomass burning (BB) (C-3 and C-4 type vegitation), secondary aerosols (SAs) and road dust (SD). The correlation analysis of δ13C with other C (OC, TC, OC/EC and OC/WSOC) components and δ15N with other N components (TN, NH4+ and NO3?) are also support the source identification of isotopic signatures.

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15.
The chemical composition of regional background aerosols, and the time variability and sources in the Western Mediterranean are interpreted in this study. To this end 2002–2007 PM speciation data from an European Supersite for Atmospheric Aerosol Research (Montseny, MSY, located 40 km NNE of Barcelona in NE Spain) were evaluated, with these data being considered representative of regional background aerosols in the Western Mediterranean Basin. The mean PM10, PM2.5 and PM1 levels at MSY during 2002–2007 were 16, 14 and 11 µg/m3, respectively. After compiling data on regional background PM speciation from Europe to compare our data, it is evidenced that the Western Mediterranean aerosol is characterised by higher concentrations of crustal material but lower levels of OM + EC and ammonium nitrate than at central European sites. Relatively high PM2.5 concentrations due to the transport of anthropogenic aerosols (mostly carbonaceous and sulphate) from populated coastal areas were recorded, especially during winter anticyclonic episodes and summer midday PM highs (the latter associated with the transport of the breeze and the expansion of the mixing layer). Source apportionment analyses indicated that the major contributors to PM2.5 and PM10 were secondary sulphate, secondary nitrate and crustal material, whereas the higher load of the anthropogenic component in PM2.5 reflects the influence of regional (traffic and industrial) emissions. Levels of mineral, sulphate, sea spray and carbonaceous aerosols were higher in summer, whereas nitrate levels and Cl/Na were higher in winter. A considerably high OC/EC ratio (14 in summer, 10 in winter) was detected, which could be due to a combination of high biogenic emissions of secondary organic aerosol, SOA precursors, ozone levels and insolation, and intensive recirculation of aged air masses. Compared with more locally derived crustal geological dusts, African dust intrusions introduce relatively quartz-poor but clay mineral-rich silicate PM, with more kaolinitic clays from central North Africa in summer, and more smectitic clays from NW Africa in spring.  相似文献   

16.
参考AP-42方法的采样规范(USEPA,2011),对武汉市13个城区的不同类型道路采集了137个扬尘样,并记录采样面积、车流情况、车道状况、地理位置、周围环境以及气象数据要素信息,得到了不同类型道路的积尘负荷,估算了其扬尘排放因子和排放量.结果表明:武汉总城区尘负荷由大到小顺序为支路 > 次干道 > 主干道 > 快速路,其中支路平均尘负荷为2.396 g/m2,快速路为0.852 g/m2,远城区平均尘负荷是主城区平均尘负荷的2倍左右.各类型道路不同粒径范围的道路交通扬尘排放因子大小顺序为支路 > 次干路 > 主干路 > 高速路,与尘负荷大小趋势一致.2016年道路交通扬尘源TSP的年排放量为156 931.4 t,PM10的年排放量为39 868.7 t,PM2.5的年排放量为11 574.8 t,其不确定性范围分别为-24.7%~31.4%、-31.3%~32.9%、-31.8%~30.5%.其中主干道扬尘排放量最大,其TSP、PM10和PM2.5的年排放量分别为64 447.1、16 372.9和4 753.4 t.  相似文献   

17.
The insular suburban site of Castillo de Bellver was selected for the study of the variability of PM levels and composition in the Western Mediterranean Basin (WMB).Mean annual (in 2004) PM10 and PM2.5 levels at this site were 29 and 20 µg/m3, respectively. These levels may be regarded as relatively low when compared with other suburban insular locations in the Eastern Mediterranean Basin (EMB), but they are higher than those recorded at most of the European suburban sites, especially in Northern and Western Europe. Seasonal variability of PM levels at this site is governed by meteorology rather than local emissions, whereas the daily cycles are clearly defined by the anthropogenic emissions, mainly coming from the urban area of Palma de Mallorca and the harbour area of the same city.Concerning the aerosol composition at this site, the main PM constituent is the mineral matter (29% in PM10 and 16 % in PM2.5), more than 50% (in PM10) being attributable to African dust. The amount of secondary inorganic aerosols is also very high (27% in PM10 and 34% in PM2.5), with the predominance of fine ammonium sulphate, and in a less proportion fine ammonium nitrate (in winter) and coarse Ca and Na nitrate (with higher importance in summer). The carbonaceous particles, dominantly fine, account for 17% of PM10 and 25% of PM2.5. The elemental carbon/organic carbon (EC/OC) ratio reached a mean value of 0.17, similar to those observed at regional background sites in the WMB coast of Spain. The sea spray aerosols (mainly coarse) represented around 10% of PM10, and only 4% in PM2.5. Finally, the unaccounted fraction increased from 15% to 20% in PM2.5, being mostly attributed to water.The concentrations of trace elements in PM10 and PM2.5 were usually in the range to those observed in regional background sites in the Iberian Peninsula, with the exception of the typical tracers of road traffic such as Cu, Sb, Zn, Sn and Ba, which presented concentrations in the range of urban sites of Iberia. Other elements such as Cr, Zr, Hf and Co have been identified as the main tracers of the harbour contributions.  相似文献   

18.
Zhang  Xiaoyu  Ji  Guixiang  Peng  Xiaowu  Kong  Lingya  Zhao  Xin  Ying  Rongrong  Yin  Wenjun  Xu  Tian  Cheng  Juan  Wang  Lin 《Journal of Atmospheric Chemistry》2022,79(2):101-115

In this study, 123 PM2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM2.5 concentration was 80.5?±?38.2 μg/m3, with higher PM2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM2.5 mass concentration, respectively. SO42?, NO3? and NH4+ were the dominant components, accounting for 40.2% of PM2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO3?/SO42? was 0.86?±?0.72, indicating that stationary sources play dominant role on PM2.5 concentration. The ratio of OC/EC was 2.9?±?1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively.

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19.
为了更好地研究沙尘气溶胶起沙和输送特征,2010年4—5月,在民勤周边沙地利用EZ LIDAR ALS300&ALS450型激光雷达和 GRIMM 180型颗粒物采样器进行了大气气溶胶的外场连续观测,取得了晴天、浮尘、扬沙和沙尘暴天气条件下沙尘气溶胶总后向散射垂直剖面图和PM10、PM2.5、PM1.0质量浓度采样资料,其中包含“0424”特强沙尘暴过程资料。结果表明:春季民勤近地层大气中沙尘气溶胶浓度较高,且随气象要素的变化很大;在整个观测期内,PM10、PM2.5、PM1.0的平均质量浓度分别为202.3、57.4 μg/m3、16.7 μg/m3。在不同天气条件下,PM10、PM2.5、PM1.0质量浓度的变化有很好的相关性,但变化趋势有所不同。在沙尘暴天气条件下,PM10的日平均质量浓度高达2469.1μg/m3,是背景天气条件下PM10日平均质量浓度的100多倍,是浮尘天气条件下PM10日平均质量浓度的8倍,是扬沙天气条件下PM10日平均质量浓度的2倍。PM2.5在沙尘暴天气下日平均质量浓度为460.3 μg/m3,是背景天气条件下PM2.5日平均质量浓度的45倍,是浮尘天气条件下PM2.5日平均质量浓度的6倍,是扬沙天气条件下PM2.5日平均质量浓度的1.4倍。PM1.0在沙尘暴天气条件下的日平均浓度为92.7 μg/m3,是背景天气条件下PM1.0日平均浓度的13倍,是浮尘天气条件下PM1.0日平均浓度的7倍,是扬沙天气条件下PM1.0日平均浓度的1.3倍。可见,风速增大时沙尘粒子浓度的增加对粒子粒径是有选择的,小粒子比重随沙尘浓度增加而相对减小,大粒子比重随沙尘浓度增加而相对增多;通过对“0424”特强沙尘暴过程的研究表明,一次沙尘暴过程往往包括沙尘暴、扬沙和浮尘天气中的两种类型;通过对激光雷达数据分析发现,在强沙尘暴发生过程当中,民勤沙地发生了非常严重的风蚀起沙现象。  相似文献   

20.
Source identification of PM2.5 particles measured in Gwangju, Korea   总被引:1,自引:0,他引:1  
The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM2.5 mass (21.5 μg m− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM2.5 sources.Additionally, the impact of air mass pathways on the PM2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM2.5 mass during the biomass burning (BB) event equaled 63.8%.  相似文献   

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