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1.
济南市空气中颗粒物来源与防治对策   总被引:3,自引:0,他引:3  
颗粒物(总悬浮颗粒物TSP及可吸入颗粒物PM10)已成为济南市空气污染的首要污染物,其主要来源为扬尘、煤烟尘和风沙尘.三类尘对TSP和PM10的贡献分别为扬尘:34%和30%、煤烟尘:25%和19%、风沙尘:18%和22%.文中在阐明颗粒物源解析的分析方法及结果基础上,提出了颗粒物污染的防治对策.  相似文献   

2.
宁波市颗粒物中多环芳烃浓度水平、分布及来源分析   总被引:1,自引:1,他引:1  
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。  相似文献   

3.
使用带能谱的高分辨率场发射扫描电镜(FESEM)和图像分析技术对奎屯—独山子区冬季PM_(2.5)样品进行微观形貌测定,研究其数量—粒度分布、体积—粒度分布特征。结果表明:单颗粒主要包含矿物颗粒、球形颗粒、烟尘集合体和其他颗粒。工厂、电厂、机动车尾气、道路扬尘是奎屯—独山子区域大气污染的主要来源。矿物颗粒对奎屯—独山子区域PM_(2.5)的数量贡献最大。各采样点各种类别颗粒物数量百分含量的不同,反映了污染物来源的不同。冬季各种颗粒主要分布在0.1~0.6μm的粒径范围内。  相似文献   

4.
南京市冬季大气颗粒态汞的分布特征   总被引:2,自引:0,他引:2  
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。  相似文献   

5.
采用石墨炉原子吸收分光光度法、双道原子荧光光谱法研究乌鲁木齐市采暖期前期与后期不同粒径大气颗粒物(TSP、PM_(10)、PM_5、PM_(2.5))中Hg、As、Zn、Pb、Ni等5种重金属元素的质量浓度,并对重金属污染水平进行评价。Hg质量浓度为0.3~5.7 ng/m3;As质量浓度为15.3~122.5 ng/m~3;Zn质量浓度为298.0~1 686.5 ng/m~3;Pb质量浓度为0.5~88.8 ng/m~3;Ni质量浓度为10.4~25.5 ng/m~3。Igeo计算得出采暖期后期的TSP、PM_(10)、PM_5、PM_(2.5)中各重金属Igeo值均高于采暖期前期,其中Hg元素为严重污染;富集因子分析得出Hg、Zn元素的EFi值大于10,说明这些元素是人为源贡献。通过研究乌鲁木齐市不同时期、不同粒径大气颗粒物中各种重金属污染状况,为乌鲁木齐大气污染治理提供科学支持。  相似文献   

6.
采用单颗粒气溶胶飞行时间质谱仪(Single Particle Aerosol Mass Spectrometer,SPAMS)对西安市大气矿尘颗粒物进行连续12 d在线分析,共采集到107 425个同时含有正负质谱信息的矿尘颗粒,矿尘颗粒物占PM_(2.5)样本数的8.44%。结果表明,矿尘颗粒物的正离子碎片成分以Na~+、K~+、Al~+、Ca~+、CaO~+、Fe~+为主,同时还含有Pb~+等,负离子碎片成分以NO~-_2和NO~-_3为主,另外还含有HSO~-_4、SiO~-_3、HSiO~-_3、H(NO_3)~-_2等。在西安市大气细颗粒物中,矿尘颗粒物中贡献较大的几类(如含钙、含铁、铁氧颗粒物等)大多是老化的成分。将观测阶段采集到的矿尘颗粒纳入本地污染源谱进行来源分析,其主要来源为扬尘源、工业源、燃煤源和汽车尾气源等。  相似文献   

7.
石家庄市大气颗粒物元素组分特征分析   总被引:2,自引:1,他引:1  
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。  相似文献   

8.
为了解石家庄市2016年春季大气颗粒物的铅污染特征及来源,利用单颗粒气溶胶质谱仪(SPAMS),分析了大气中含铅颗粒的化学成分。结果表明: 研究期间大气环境中含铅颗粒数浓度共出现11次跳跃式升高,跳跃时间段内石家庄均处于轻度污染过程。从成分分析来看,含铅颗粒分为纯铅颗粒、Pb与K(Pb-K)、OC(Pb-OC)、Cl(Pb-Cl)、混合颗粒等八大类。观测结果表明:Pb-K颗粒最多,占到含铅颗粒的84.4%;其次为纯铅颗粒,占比为13.0%。与石家庄市污染源谱库比对进行来源解析,得到Pb-K颗粒主要来自生活垃圾焚烧源, 纯铅颗粒主要来自工业源。结合石家庄市大气污染源排放清单和后向气流轨迹分析,推测含铅颗粒可能来自市区西南方向某区县的生活垃圾焚烧企业。  相似文献   

9.
分析探讨了乌鲁木齐市采暖期大气颗粒物中TSP、PM_(10)和PM_(2.5)的含量,对颗粒物样品进行分级提取,测定Hg,As,Pb,Cd的存在形态。结果表明,不同区域中的重金属元素存在形态分布差别较大,不同粒径颗粒物中的重金属形态各不相同,质量分布亦有明显差异。  相似文献   

10.
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   总被引:3,自引:2,他引:1  
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。  相似文献   

11.
乌鲁木齐市米东污灌区农田土壤重金属污染评价   总被引:7,自引:0,他引:7  
对米东污灌区农田土壤重金属含量进行监测分析,利用不同的评价方法和标准对土壤重金属的环境质量进行评价。结果表明:米东污灌区农田土壤重金属含量分别为Cd(0.12±0.06)mg/kg,Cu(40.43±5.30)mg/kg,Zn(78.38±11.04)mg/kg,Pb(11.66±11.79)mg/kg,Ni(20.24±8.05)mg/kg,Cr(75.81±8.05)mg/kg。以国家土壤环境质量标准(二级)为标准评价,各元素的污染指数排序为Cu>Ni>Cr>Zn>Cd>Pb,综合污染指数为0.337,污染程度为安全。以食用农产品产地土壤环境质量要求为标准评价,各元素的污染指数排序为Cu>Ni>Cr>Zn>Cd>Pb,综合污染指数为0.343,污染程度为安全。表明米东污灌区农田土壤重金属含量尚能达到食用农产品产地土壤环境质量要求。Pb、Cu、Zn的平均含量超过乌鲁木齐市土壤背景值,这说明污灌区土壤重金属Pb、Cu、Zn近年来已有所累积,存在一定的污染风险。  相似文献   

12.
南京市建筑扬尘排放清单研究   总被引:4,自引:0,他引:4  
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。  相似文献   

13.
南京市城区环境空气中总悬浮颗粒物的源解析   总被引:10,自引:0,他引:10  
应用受体模式的化学质量平衡法(CMB),对南京市城区7个环境监测点环境空气中的总悬浮颗粒物(TSP)进行污染源的源解析,得出4类主要污染源对TSP的平均贡献率,建筑尘39.8%、煤烟尘25.7%,土壤尘19.2%,冶炼尘1.8%,同时,对该市城区的地面尘也进行了源解析,表明地面尘与环境中TSP的构成相近。  相似文献   

14.
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.  相似文献   

15.
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.  相似文献   

16.
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.  相似文献   

17.
因子分析法解析北京市大气颗粒物PM10的来源   总被引:17,自引:3,他引:17  
2004年10月份在北京市6个采样点采集了大气PM10样品,分析了大气颗粒物的质量浓度、元素组成、离子、有机碳(OC)和元素碳(EC)的浓度,并用因子分析模型对颗粒物的来源进行了研究。结果显示,北京市大气颗粒物的来源主要有6类:建筑水泥尘/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘、生物质燃烧尘和燃油尘。用模型计算得到的各源对PM10的贡献率分别为建筑水泥尘/机动车尾气尘/燃煤尘占36.57%、土壤风沙尘占16.07%、二次粒子尘占12.33%、工业粉尘占10.29%、生物质燃烧尘占6.07%、燃油尘占3.84%、其它占14.84%。其中建筑水泥/机动车尾气尘/燃煤尘、土壤风沙尘、二次粒子尘、工业粉尘是大气颗粒物PM10的主要来源。实验表明,在缺少源成分谱时可以用因子分析模型来分析大气颗粒物的来源及其相对贡献。  相似文献   

18.
宁波和温州地区夏季大气中不同粒径颗粒物特征分析   总被引:1,自引:0,他引:1  
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%。  相似文献   

19.
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.  相似文献   

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