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1.
根据南通市大气超级站的观测结果和气象因素,对南通市2019年10月29日—11月2日一次典型沙尘污染过程、颗粒物化学组分、颗粒物消光和退偏进行分析。结果表明,在沙尘影响期间,PM10小时峰值达311 μg/m3, ρ(Ca2+)较污染前上升了7.4倍;在沙尘颗粒物碱性环境条件下,二次组分OM和NO-3的快速生成,浓度分别较污染前上升了96.6 %和34.0 %;ρ(NO-3)/ρ(SO-24)污染中(2.5)高于污染前(1.7),ρ(EC)/ρ(PM2.5)污染中(4.2%)高于污染前(3.6%),受到明显的沙尘传输影响,而移动源排放也有一定贡献,在本地地面气压场较弱情况下,导致沙尘污染过程长时间持续。  相似文献   

2.
分别于2013年10月和2014年2月、5月、7月在贵阳市城区3个环境空气质量监测国控点位(南明区市监测站、云岩区黔灵公园马鞍山和观山湖区贵阳一中)进行PM10、PM2.5样品采集,并对10种水溶性离子(SO42-、NO2-、NO3-、NH4+、Cl-、F-、Na+、K+、Mg2+、Ca2+)的含量进行了分析。结果表明,研究时段内,贵阳市3个点位PM10、PM2.5平均质量浓度分别为(64.8±25.5)、(46.6±21.2)μg/m3。其中,云岩区黔灵公园马鞍山点位的颗粒物浓度最低,南明区市监测站点位最高。3个点位PM2.5平均浓度与PM10平均浓度的比值为0.719,表明贵阳市城区PM10中,PM2.5占主导地位。水溶性离子分析显示,SO42-、NO2-、NO3-、NH4+、Cl-、F-、Na+、K+主要分布在PM2.5中,Mg2+、Ca2+主要分布在PM10中。3个点位PM10和PM2.5中的水溶性离子均表现为SO42-、NH4+、Ca2+浓度较大,F-、NO2-较小,表明3个点位的污染源总体相同,且水溶性离子占PM10、PM2.5含量的比例达33.6%~48.1%。贵阳市城区大气中的SO2转化率在5月、7月、10月较高,2月最低,主要是由于5月、7月、10月的高温、高湿、强辐射环境条件促进了SO2向SO42-的转化。阴阳离子平衡分析表明,贵阳市城区PM10、PM2.5呈现出偏碱性的特征。水溶性离子主成分分析表明,贵阳市城区PM10中的水溶性离子主要来源于城市扬尘、生物质燃烧尘、煤烟尘、建筑尘以及二次粒子,PM2.5中水溶性离子的来源与PM10较为相似。  相似文献   

3.
天津市PM2.5中水溶性离子组分特征   总被引:2,自引:1,他引:1  
2006年8—12月连续采集PM2.5样品,分析其中水溶性无机离子浓度特征。结果表明,采样期间,天津市PM2.5日均浓度均不同程度超过美国EPA日均浓度标准(35 μg/m3);SO42-、NO3-、NH4+和Cl-为无机离子的主要成分,占全部无机离子的88.6%;各离子均表现出不同季节变化特征。对NH4+和NO3-、SO42-进行相关性分析发现,NH4+和NO3-相关性最好,相关系数为0.795。SOR和NOR的平均值分别为0.16和0.23,均为8月最高,表明前体物二次转化夏季最明显。  相似文献   

4.
为了研究北京大气颗粒物和二NFDA1英(PCDD/Fs)的污染状况以及评估交通限行对大气颗粒物和PCDD/Fs的影响。利用同位素稀释高分辨率气相色谱/高分辨率质谱(HRGC/HRMS)联用法和USEPA 1613B 标准方法,以中国地质大学(北京)东门为采样点,采集大气PM2.5、PM10、TSP样品,对北京市交通限行期间以及交通限行前后等不同交通状况下颗粒物浓度及大气PM2.5中17种2,3,7,8-PCDD/Fs污染特征进行了监测。结果表明,PM2.5、PM10、TSP的日均质量浓度在交通限行前分别为126、202、304 μg/m3,限行期间分别为39、78、93 μg/m3,限行结束后分别为79、126 μg/m3。PM2.5中17种PCDD/Fs的质量浓度(毒性浓度)3个时段分别为1 804 fg/m3(70 fg I-TEQ/m3)、252 fg/m3 (9 fg I-TEQ/m3)和1 196 fg/m3 (48 fg I-TEQ/m3)。北京市交通限行期间颗粒物浓度和二 NFDA1 英浓度显著低于交通限行前后,交通源减排措施的实施是大气颗粒物和二 NFDA1英污染水平降低的主要原因,从减排效果看,交通源减排措施对大气细颗粒物(PM2.5)的控制效果明显好于大气粗颗粒物。  相似文献   

5.
北京夏季大气主要含氮无机化合物的变化规律与相互作用   总被引:5,自引:2,他引:3  
利用SJAC-MOBIC/FIA在2006年8月16日—9月9日在线测量了北京城市大气细颗粒物中主要水溶性含氮离子组分(NO3-和 NH4+),与重要含氮气态污染物(HNO3、HNO2和 NH3),以追踪细颗粒物中含氮二次无机组分和含氮气态污染物的变化规律及其相互作用。观测期间,NO3- 和 NH4+的平均浓度分别为13.08和11.93 μg/m3,它们与SO42-浓度之和在细颗粒物(PM2.5)中的平均比例为55%,明显高于其他季节;污染过程中,积聚模态颗粒物体积浓度及其与爱根核模态颗粒物体积浓度比值逐渐增加,说明二次转化是北京夏季细颗粒物的重要来源。白天HONO迅速光解产生OH自由基,而OH自由基是生成HNO3的重要物种,因此HONO和HNO3具有相反的日变化规律。在温度较高的白天,大气环境不利于NH4NO3的生成与存在;夜间低温高湿的条件下硝酸铵理论平衡系数Ke与气态氨和硝酸的乘积Km相当或低于后者,较有利于NH4NO3的生成。北京夏季大气具有足量气态NH3以中和硫酸盐;但在NO3-与阳离子的电荷平衡中,金属阳离子也非常重要。  相似文献   

6.
南京大气细颗粒物中水溶性组分的污染特征   总被引:4,自引:3,他引:1  
为了解南京城区大气细颗粒物中水溶性组分的污染特征,在国控点草场门进行了连续一年的PM2.5采样与分析。6种离子日均浓度为5.29~67.6 μg/m3,其中SO42-、NH4+、NO3-是PM2.5的主要组成成分,6 种离子约占PM2.5总质量的31%,SO42-、NO3-和NH4+相关性较好,NH4+是PM2.5中硫酸盐和硝酸盐中居于主导地位的离子。  相似文献   

7.
北京市PM2.5质量浓度特征及组分化学质量闭合研究   总被引:1,自引:1,他引:0  
2013年7—9月分2次在北京市朝阳区的4个采样点(来广营、垡头、奥体和建外)进行PM2.5手工采样,共获得164个有效滤膜样品。以石英滤膜为例,这4个采样点的均值分别为85、94、81、86 μg/m3。数据显示PM2.5质量浓度呈"南高北低"的特点。化学质量闭合研究表明:碳质组分(OM+EC)和二次无机离子是PM2.5的主要组成;碳质组分对夏季PM2.5的质量浓度贡献比较稳定,2次采样对PM2.5的贡献均在1/3左右,与采样时间和地点无关;二次无机离子的贡献则与采样时间有关,对PM2.5的贡献在第一和第二次采样时间分别约为30%和20%。4个采样点中,最南端的垡头PM2.5质量浓度最高,有机颗粒物、SO42-、NO3-和NH4+的质量浓度平均值最高,分别为26、18.2、10.5、5.9 μg/m3。  相似文献   

8.
天津市PM2.5中水溶性无机离子污染特征及来源分析   总被引:7,自引:2,他引:5  
2008年1、4、7月和10月在天津大气层边界站,利用中流量采样器对大气中的细粒子进行了滤膜样品采集,应用离子色谱检测技术分析了8种水溶性无机离子(Na+、NH4+、K+、Mg2+、Ca2+、SO42-、NO3-和Cl-)的含量。结果表明,天津市大气PM2.5中总水溶性无机离子平均浓度为47.3 μg/m3,其中,SO42-、NO3-、NH4+和Cl-是最主要的水溶性无机离子,占总离子质量分数共计87.3%,表明了天津市细粒子中的主要水溶性无机离子的特征。/2 平均比值接近1.0,显示硫酸氨是细粒子中硫酸盐的主要存在形式。NO3-/SO42-浓度比的平均值为0.65,反映了燃煤污染与机动车尾气污染并存的复合型大气污染特征。并通过对PM2.5中8个水溶性离子成分的主成分分析进一步揭示了其来源。  相似文献   

9.
通过对比2021年春节烟花爆竹集中燃放时段和前期非集中燃放时段的PM2.5浓度及特征组分浓度,分析了烟花爆竹集中燃放对陕西省PM2.5的影响情况。分析结果显示,2021年春节烟花爆竹集中燃放时段,关中和陕南地区PM2.5浓度增幅大且高值持续时间长,陕北地区PM2.5浓度增幅小且高值持续时间短。陕北和陕南地区PM2.5小时浓度峰值出现在2月12日(初一)00:00前后,关中地区略晚。西安市PM2.5特征组分中,K+、Cl-、SO42-、NO3-、Mg2+、Al3+、Cu2+、Si2+、Ba2+的浓度分别为6.61、7.20、12.83、23.96、1.36、2.91、0.23、0.27、0.86 μg/m3,明显高于非集中燃放时段。烟花爆竹燃放对陕南地区PM2.5的贡献率和贡献量均高于关中和陕北地区;对郊县PM2.5的贡献率高于城区,且对郊县的贡献率正值的出现时间早于城区。除榆林市外,陕西省其他城市的城区均受到了相关郊县烟花爆竹燃放的影响。  相似文献   

10.
基于周口市2021年冬防期间(2021年10月1日—2022年3月31日)4个国控站点的在线小时数据和日均数据,利用统计和相关性分析等方法,研究了冬防期间污染要素的时空变化特征及其与主要气象因子之间的相关性。结果表明,周口市2021冬防期间空气质量达标率为64.8%,主要污染物为细颗粒物(PM2.5),其中1月的大气污染最严重,ρ(PM2.5)小时平均值为120 μg/m3,可吸入颗粒物(PM10)质量浓度小时最高值出现在3月沙尘期间,为591 μg/m3。各污染要素的变化整体趋同,但多个站点的ρ(SO2)和ρ(NO2)频繁出现短时高值,这一现象可能与局地细颗粒物污染相关,在后续大气污染防控中需引起重点关注。市运管处站的NO2和SO2质量浓度整体偏高,需关注周边机动车相关的颗粒物排放。此外,西北风和东风对于PM2.5污染传输的影响较大,气象不利条件下,需要加强管控,以有效保证空气质量达标。  相似文献   

11.
超低排放下燃煤电厂颗粒物排放特征分析研究   总被引:4,自引:0,他引:4  
选取6家经过超低排放改造的燃煤电厂,对湿法脱硫(WFGD)和湿式电除尘器(WESP)进出口烟气中TPM、PM_(10)、PM_(2.5)、PM_1进行测试,分析研究超低排放下燃煤电厂颗粒物的排放特征及电除尘器后净化设备对颗粒物的脱除效果。结果表明,6家电厂TPM、PM_(10)、PM_(2.5)、PM_1排放浓度分别为0.75~2.36、0.71~2.12、0.65~1.96、0.51~1.57 mg/m~3。分析烟气中颗粒物粒径分布可知,除尘器后,PM10占TPM质量比低于40%,且比例随烟气经过WFGD和WESP而逐渐降低。WFGD对PM2.5有较好的脱除效果,而WESP对PM1脱除效果显著。为满足超低排放标准,6家电厂除尘器后脱除设备综合除尘效率大多在85%以上。计算得到6家电厂TPM、PM_(10)、PM_(2.5)、PM_1排放因子,与超低排放改造之前同等级燃煤电厂相比,6家电厂不同粒径颗粒物排放因子均显著降低,也远低于西方发达国家燃煤电厂颗粒物排放因子。  相似文献   

12.
Temporal and spatial variations in particulate organic carbon (POC) in relation to primary production, chlorophyll a, phaeophytin, plankton abundance, secondary production and suspended particulate matter (SPM) were studied monthly for 1 year from April 1996 to March 1997 in a shallow tropical coastal lagoon on the southwest coast of India. Though temporal variations in all components were significant, spatial variabilities were not statistically significant. POC values range from 200 to 5690 mg C m3 h−1, while primary production, chlorophyll a, and phaeophytin varied between 0.02 and 14.53 mg C m−3 h−1, 0.87 and 23.11 mg m−3 and 3.02 and 30.581 mg m−3, respectively. Phytoplankton and zooplankton abundance varied from 0.01 to 655.5×105 no m−3 and negligible to 7.08×105 no m−3 respectively; secondary production from 10 to 490 mg C m−3 and SPM between 0.38 and 74.43×104 mg m−3 during this study. Temporally, postmonsoon months were observed to have the highest concentrations of POC in the lagoon waters. The bulk of the POC pool in the lagoon was composed of secondary producers (72%), followed by chlorophyll a (21%), phaeophytin (7%) and suspended particulate matter of inorganic origin (< 0.1%).  相似文献   

13.
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.  相似文献   

14.
The concentrations of criteria air pollutants such as CO, NOx (NO + NO2), SO2 and PM were measured in the period of May 2001 and April 2003 in the city of Bursa, Turkey. The average concentrations for this period were 1115±1600 μg/m3, 29±50 μg/m3, 51±24 μg/m3, 79±65 μg/m3, 40±35 μg/m3, 98±220 μg/m3, for CO, NO, NO2, NOx, SO2 and PM, respectively. Temporal changes in concentrations were analyzed using meteorological factors. Correlations among pollutant concentrations and meteorological parameters showed weak relations nearly in all data. Lower concentrations were observed in the summer months while higher concentrations were measured in the winter months. The increase in winter concentrations was probably due to residential heating. Pollutants were associated with each other in order to have information about their origin. NOx/SO2 ratio was also examined to bring out the source origin contributing on air pollution (i.e., traffic or stationary).  相似文献   

15.
Aerosol samples for dry deposition and total suspend particulates (TSP) were collected from August to November of 2003 in central Taiwan. Ion chromatography was used to analyze the related water-soluble ionic species (Cl, NO3 , SO4 2−, Na+, NH4 +, K+, Mg2+ and Ca2+). The results obtained in this study indicated that the ambient air particulate mass concentrations in the daytime period (averaged 975.4 μg m−3) were higher than the nighttime period (averaged 542.1 μg m−3). And the daytime dry deposition fluxes (averaged 58.12 μg m−2 sec−1) were about 2.2 times as that of nighttime dry deposition fluxes (averaged 26.54 μg m−2 sec−1) of the downward dry deposition. The average values downward and upward of dry deposition fluxes for the weekend period were almost higher than the weekday period for either daytime or nighttime period. Furthermore, the average daytime dry deposition fluxes (averaged 26.37 μg m−2 sec−1) were also about 2.3 times as that of nighttime dry deposition fluxes (averaged 11.52 μg m−2 sec−1). Moreover, the results also indicate that SO4 2− and Ca2+ have higher average composition for total suspended particulates in the daytime period while Ca2+, SO4 2−, and Na+ have the higher average composition for total suspends particulates in the nighttime period.  相似文献   

16.
基于北京市PM2.5和PM10质量浓度、组分浓度以及降水数据,利用数理统计、相关性分析等方法分别从降水总量、降水时长和降水前颗粒物浓度3个角度研究降水对PM2.5、PM10的清除作用,同时以一次典型降水过程为例,具体分析降水对颗粒物的影响。结果表明:降水总量的增加有助于促进PM2.5、PM10的清除,随着降水总量增加,PM2.5、PM10的平均清除率提高,有效清除的比例增加;连续降水可增强对大气颗粒物的湿清除作用,连续降水达3d可有效降低PM2.5、PM10浓度;降水对PM2.5、PM10浓度的清除率和大气颗粒物前一日的平均浓度有较好的正相关性。降水对大气颗粒物的清除可分为清除、回升和平稳3个阶段,各个阶段大气颗粒物的变化趋势不同。降水对于大气气溶胶化学组分和酸碱性的改变具有明显作用,对于大气颗粒物各种组分的清除效果不完全相同。对于大气中OC、NO3-、SO42-和NH4+去除率较高,且这4种组分主要以颗粒态形式被冲刷进入降水中,加剧了北京市降水酸化程度。  相似文献   

17.
Atmospheric aerosol particles and metallic concentrations, ionic species were monitored at the Experimental harbor of Taichung sampling site in this study. This work attempted to characterize metallic elements and ionic species associated with meteorological conditions variation on atmospheric particulate matter in TSP, PM2.5, PM2.5–10. The concentration distribution trend between TSP, PM2.5, PM2.5–10 particle concentration at the TH (Taichung harbor) sampling site were also displayed in this study. Besides, the meteorological conditions variation of metallic elements (Fe, Mg, Cr, Cu, Zn, Mn and Pb) and ions species (Cl, NO3 , SO4 2−, NH4 +, Mg2+, Ca2+ and Na+) concentrations attached with those particulate were also analyzed in this study. On non-parametric (Spearman) correlation analysis, the results indicated that the meteorological conditions have high correlation at largest particulate concentrations for TSP at TH sampling site in this study. In addition, the temperature and relative humidity of meteorological conditions that played a key role to affect particulate matter (PM) and have higher correlations then other meteorological conditions such as wind speed and atmospheric pressure. The parameter temperature and relative humidity also have high correlations with atmospheric pollutants compared with those of the other meteorological variables (wind speed, atmospheric pressure and prevalent wind direction). In addition, relative statistical equations between pollutants and meteorological variables were also characterized in this study.  相似文献   

18.
In recent years, suspended particle pollution has become a serious problem in Taiwan. The carbonaceous materials EC and OC are play important roles in various atmospheric processes. The primary OC/EC ratio approach is applied to assess the contribution of secondary organic aerosol (SOA) to the PM2.5 and PM10 mass at the Taichung harbor sampling site. The results indicated that the average EC and OC concentration were 1.06 and 6.50 μg m−3, respectively, in fine particulate. And the average EC and OC concentration were 4.04 and 40.32 μg m−3, respectively, in coarse particulate at Taichung Harbor sampling site. In addition, and the average EC/OC rations was 8.72 in fine particle, respectively, at Taichung Harbor, Taiwan during summer and autumn period of 2005. The fine particle exhibited high particulate concentrations in October, and lower concentration particulate occurred in August. And in this study OC and EC concentrations in this study are compared with those in other cities. The results of EC and OC concentration in this study are also compare with those other cities.  相似文献   

19.
Measurement of the exhaust emission from gasoline-powered motor vehicles in Bangkok were performed on chassis dynamometer. A fleet of 10 vehicles of different model, years and manufacturers were selected to measure the air pollutants in the exhaust effluent. The study revealed that the carbon monoxide and hydrocarbon emissions averaged 32.3–64.2 and 1.82–2.98 g km–1, respectively, for 1990–1992 cars and decreased to 17.8–40.71 and 0.75–1.88 g km–1, respectively, for 1994–1995 cars. A monitoring program for air pollutant concentrations in ambient air was also conducted to evaluate the air pollution problems in Bangkok arising from vehicle exhaust emission. Four air sampling stations were strategically established to cover the Bangkok Metropolitan Region (BMR). Composite air samples in this study area were collected during the day/night times and weekday/weekend. The average concentrations of suspended particulate matter, carbon monoxide, and nitrogen dioxide in Bangkok street air were found to be 0.65 mg/m3 (24 hr ave.), 19.02 mg/m3 (8 hr ave.) and 0.021 mg/m3 (1 hr ave.), respectively. The average concentrations of benzene and toluene in the ambient air of the study area were found to be 15.07–50.20 and 25.76–130.95 g/mf3, respectively, for 8 hr average. These results indicated that there was a significant increase in air pollutant emissions with increasing car mileage and model year. Subsequent analysis of data showed that there were only 20% of the test vehicles complied to approved emission standard. The finding also revealed that there was a correlation between the average air pollutant concentrations with average traffic speed in each traffic zone of the Bangkok Metropolitan Region (BMR).  相似文献   

20.
为研究北京地区冬季PM_(2.5)载带的水溶性无机离子组分污染特征,2013年1月在中国环境科学研究院内采用在线离子色谱(URG-9000B,AIM-IC)对PM_(2.5)中水溶性无机离子(SO_4~(2-)、NO_3~-、Cl~-、NH_4~+、Na~+、K~+、Mg~(2+)、Ca~(2+))进行监测与分析。结果表明,采样期间总水溶性无机离子(TWSI)浓度为61.0μg/m~3,其中二次无机离子SO_4~(2-)、NO_3~-、NH_4~+(SNA)占比达72.3%,在PM_(2.5)中占比为40.29%,表明北京市PM_(2.5)二次污染严重。重污染天[NO_3~-]/[SO_4~(2-)]表明,固定源污染较移动源更为显著。三元相图表明,在空气质量为优的情况下,NH_4~+(在SNA中占比为30.3%~65.5%,下同)主要以NH_4NO_3的形式存在,较少比例以(NH_4)_2SO_4存在;严重污染时,NH_4~+(47.3%~77.9%)主要以(NH_4)_2SO_4形式存在,其次以NH_4NO_3的形式存在,其余的NH_4~+以NH_4Cl的形式存在。[NO_3~-]/[SO_4~(2-)]日变化表明,早、晚机动车高峰影响北京重污染发生。  相似文献   

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