南京市气溶胶PM2.5一次来源解析

在南京大学鼓楼校区（市区）和南京信息工程大学（郊区）校园,分季采集PM2.5及其主要排放源的颗粒样品,在南京大学现代分析测试中心用X-荧光分析法分析样品中的化学元素,应用化学元素平衡法（CMB）计算了各主要源对PM2.5的贡献。结果表明对市区扬尘和建筑尘是PM2．5最主要的贡献源,贡献率合计约70％;燃煤尘和冶炼尘仅为约15％。对郊区扬尘和煤烟尘是PM2．5的最主要贡献源,平均贡献率分别为50％和22．4％,建筑尘的平均贡献率为8．3％,冶炼尘的贡献小于8％。这些结果可为治理气溶胶细颗粒源提供决策依据。     

武汉市源成分谱特征研究

通过采集武汉市土壤风沙尘、建筑水泥尘、城市扬尘、餐饮源、生物质燃烧源、工业煤烟尘和电厂煤烟尘等7类源样品,并分析其碳组分、水溶性离子组分和无机元素组分,建立PM₁₀和PM_2.5源成分谱.研究表明,地壳元素Si、Ca、Al以及Fe等是土壤风沙尘的主要特征组分,其中Si是含量最高的成分,也是土壤风沙尘的标识组分.无组织建筑水泥尘中Si和Ca元素含量较高,将Ca元素作为无组织建筑水泥尘区别其他源类的重要元素,而有组织建筑水泥尘中OC、SO₄^2-含量比无组织建筑水泥尘高.城市扬尘中Ca的含量相对较高,表明城市扬尘受到建筑水泥尘影响较多.生物质燃烧源成分谱中OC的含量远高于成分谱中其他组分,另外Cl^-和K的平均含量也较高,K一般为生物质源的特征元素.     

南京市PM2.5物理化学特性及来源解析

在夏、冬两季,分别在南京市4个站点进行为期7天的气溶胶PM2.5采样,同步采集并分离主要排放源的PM2.5样品,用X射线荧光光谱仪(XRF)分析得到气样及源样中PM2.5的化学成分,对南京市PM2.5的物理化学特性、富集因子进行了分析,并应用化学质量平衡法(CMB)计算各类源对气溶胶PM2.5的贡献。结果表明,南京市PM2.5的夏、冬平均值分别为69.1、139.5μg.m-3,PM2.5/PM10的全年平均值为63.9%;富集成分中,S、As、Zn、Pb等主要来源于人为污染源,Na则主要来源于海洋。来源解析的结果表明,各类污染源对南京市气溶胶PM2.5的贡献率分别为:扬尘37.28%、煤烟尘30.34%、硫酸盐9.87%、建筑尘7.95%、汽车尘2.98%、冶炼尘2.57%、其他源9.01%。作者还对扬尘中的PM2.5进行了来源解析。     

南京市主城区大气颗粒物来源探讨

在2005-05-03——05-27期间,用Anderson九级采样器在南京市两个采样点采集大气气溶胶样品,同时进行了部分排放源的采集。用X射线—荧光光谱仪(XRF)分析得到气样及源样中PM10的化学成分,分析了南京市大气气溶胶的元素质量谱分布,进行了PM10的富集因子分析,并应用化学质量平衡法(CMB)计算各类源对气溶胶PM10的贡献。结果表明,各类污染源对南京市气溶胶PM10的贡献率分别为:建筑尘(35.45%)、煤烟尘(22.13%)、土壤尘(20.27%)、硫酸盐(5.43%)、汽车尘(4.61%)、海盐(1.91%)、冶炼尘(1.69%)、其它源(8.51%)。文中还结合了南京市TSP和PM2.5的来源解析结果,分析了南京市不同粒径气溶胶颗粒物的污染特征。     

2004年北京秋季大气颗粒物的化学组分和来源特征

2004年9月在北京城区进行了大气颗粒物采样,样品用PIXE方法进行了分析,得到了20种元素的浓度及其谱分布。并对北京颗粒物的谱分布、富集因子和来源进行了分析研究。发现K元素浓度分布呈细粒态单峰谱分布,细粒态K富集因子较高,表明了生物质燃烧的主要贡献。因子分析结果还表明,土壤尘、生物质燃烧、煤烟尘、工业源和汽车尾气排放源对秋季北京局地排放源有明显贡献。     

气候变化对河北坝上地区草地土壤风蚀扬尘季节和年排放速率的影响

以全球气候模式NorESM1-M产生的RCP2.6、RCP4.5、RCP6.0、RCP8.5气候变化情景数据和原环保部推荐的土壤风蚀扬尘计算方法,模拟分析了未来气候变化对河北坝上砂粘壤土、粘壤土、壤粘土、砂壤土、砂粘土和风沙土草地土壤风蚀扬尘总可悬浮颗粒物(Total Suspended Particle,TSP)、PM10和PM2.5的季节及年排放速率的影响。结果表明:气候变化影响下坝上地区气温上升,年降水量和风速波动较大、并存在上升和下降的趋势。相比基准情景,在RCP2.6、RCP4.5、RCP6.0和RCP8.5情景下,各土壤风蚀扬尘TSP、PM10和PM2.5季节排放速率在春季分别高15%、47%、28%和46%;秋季分别高17%、54%、45%和38%;冬季分别低36%、42%、39%和44%;夏季,在RCP2.6情景下低1%,在RCP4.5、RCP6.0和RCP8.5情景下分别高14%、3%和7%;未来气候变化情景下,各土壤风蚀扬尘TSP、PM10和PM2.5年排放速率分别高25%、54%、35%和54%。基准和未来气候变化情景下,土壤风蚀扬尘TSP、PM10和PM2.5的季节和年排放速率及其差异从高到低均依次为砂粘壤土、风沙土、砂壤土、粘壤土、壤粘土和砂粘土。表明未来气候变化将使河北坝上地区草地土壤风蚀扬尘排放速率增加,但存在季节和气候变化情景方面的差异。     

华北典型农业区PM2.5组分分析与来源解析

华北大气污染区域化正在对农业生态区域产生显著影响,为了了解华北农业地区大气细颗粒物PM2.5的季节分布特征,2017年7月、9月、12月以及2018年4月在中国科学院禹城农业生态综合实验站进行分季节PM2.5样品采集,并测定分析了样品中31种化学成分.结果表明,碳质气溶胶总体的浓度水平为13.11±8.37μg m-3,有机碳(OC)冬春季节浓度较高,元素碳(EC)浓度在秋冬季节较高.同时OC/EC的比值在秋季明显偏低,表明在秋季二次碳质气溶胶对PM2.5贡献较小.水溶性离子浓度总体在冬季最高.NO3-/SO2-4比值在夏季明显偏低为0.69,华北地区夏季固定点源对大气污染的贡献相对较高.PM2.5中金属元素以Na、Mg、Al、Ca、K、Fe等地壳元素为主,具有致癌风险的Co、Cr、Ni、Pb、As等金属元素年均浓度为0.32±0.24 ng m-3、5.40±5.42 ng m-3、10.23±7.46 ng m-3、42.23±27.75 ng m-3、5.66±3.79 ng m-3.受体模型(PMF)计算结果表明,PM2.5的主要来源为二次污染源、生物质燃烧源、燃煤燃油源、柴油车尾气和土壤源,贡献率分别达37.1％、18.2％、14.2％、9.4％和7.9％,表明农业区细颗粒物污染受到华北工业、农业与自然排放的多重影响.     

北京秋季气溶胶化学成分的高分辨率观测及来源分析

2001年9月30日～10月6日在北京北三环和北四环之间的中国科学院大气物理研究所气象塔院内使用步进采样仪对气溶胶进行了高分辨率连续采样(每2h采集1个样品),并对样品用PIXE方法进行了元素分析,得到20种元素的浓度。分析结果表明,气溶胶各元素浓度随时间的变化趋势基本一致,且日变化特征显著,早晚出现峰值。降雨期间Ti、Si、Fe等元素浓度急剧下降。S、Pb、Cl、Zn等与人类活动相关的气溶胶元素的富集因子很高。因子分析结果表明,北京秋季大气气溶胶主要源于土壤尘、燃煤尘、工业源和汽车尾气排放等。     

天津大气气溶胶化学组分的粒径分布和垂直分布

2006年8月在天津气象铁塔的10、120、220 m 3个不同高度.利用Andersen分级采样器同步进行大气气溶胶采样,样品用离子色谱和电感耦合等离子体质谱仪进行分析.结果表明,K元素主要集中在细粒子,Mg、Ca、Al、Fe元素主要集中在粗粒子,Na元素则具有双峰结构;总离子浓度随着高度的升高有增加的趋势,SO42-、N3-、NH4+、Ca2+是最主要的水溶性尤机离子;二次源是水溶性离子重要的贡献源.NO3-、SO42-、NH4+随着高度升高,浓度有向小粒径集中的趋势;各层气溶胶阴阳离子平衡值小于1,表明气溶胶偏碱性,与天津地处北方,土壤偏碱性,且非采暖期地面扬尘是主要的气溶胶来源有关;各层NO3-/SO42-平均值为0.48,表明非采暖期固定排放源(燃煤)仍然是天津大气细粒子中水溶性离子的主要来源.     

有关气溶胶细粒子对城市能见度影响的研究

文章介绍了国外关于大气气溶胶细粒子对城市能见度影响的研究情况。城市能见度降低问题是由气溶胶PM10、PM2.5和NO2气体引起的。影响城市能见度的颗粒物的主要来源是：机动车尾气（29％）、煤灰（18％）、二次硫酸盐（17％）、生物质燃烧（10％），自然源、海盐、土壤/公路边灰尘各贡献（2％）。     

武汉市一次霾污染过程不同发展阶段下水溶性离子来源解析

本文利用气体组分及大气气溶胶在线监测系统(MARGA ADI 2080)观测武汉市2018年1月9—26日大气气溶胶中的8种水溶性离子(NH⁺₄、NO^-₃、SO^2-₄、Cl^-、K⁺、Ca²⁺、Na⁺和Mg²⁺),结合气象要素数据,使用主成分分析(PCA)、正定矩阵因子分析法(PMF)、HYSPLIT后向轨迹模式、潜在源区贡献(PSCF)和浓度权重轨迹(CWT),对霾污染过程中水溶性离子进行了全面的来源解析,探究了霾不同阶段下来源差异和空间分布特征。结果表明:(1)本次霾污染中的8种水溶性离子和4种污染气体,PCA解析出的源和占比分别为二次源和燃煤源的混合源(41.28%)、工业排放和土壤扬尘混合源(27.73%)和机动车排放源(9.63%),PMF解析出的源和占比分别为燃煤与土壤扬尘混合源(18.57%)、机动车排放源(20.74%)、二次源(18.30%)、光化学污染源(22.24%)和燃煤源(20.15%)。(2)霾在不同阶段下水溶性离子和4种污染气体的来源存在差异,在清洁天和霾消散阶段,光化学的贡献最高,占比分别为31.42%和36.07%;在霾发生阶段燃煤与土壤扬尘源的贡献最高,其贡献为40.94%;在霾发展阶段,最大的控制源为二次源,贡献占比为37.51%。(3)此次武汉市霾污染中PM_2.5浓度和NH⁺₄、NO^-₃和SO^2-₄的潜在源区为皖豫鄂三省和赣湘鄂三省交界处。霾污染中PM_2.5的主要影响范围是武汉市南部和北部省份,NO^-₃、NH⁺₄和SO^2-₄的主要影响区域为武汉市东北方向的城市、湖南省和江西省。     

Chemical composition of PM2.5 at an urban site of Chengdu in southwestern China

PM2.5 aerosols were sampled in urban Chengdu from April 2009 to January 2010, and their chemical compositions were characterized in detail for elements, water soluble inorganic ions, and carbonaceous matter. The annual average of PM2.5 was 165g m－3, which is generally higher than measurements in other Chinese cities, suggesting serious particulate pollution issues in the city. Water soluble ions contributed 43.5% to the annual total PM2.5 mass, carbonaceous aerosols including elemental carbon and organic carbon contributed 32.0%, and trace elements contributed 13.8%. Distinct daily and seasonal variations were observed in the mass concentrations of PM2.5 and its components, reflecting the seasonal variations of different anthropogenic and natural sources. Weakly acidic to neutral particles were found for PM2.5. Major sources of PM2.5 identified from source apportionment analysis included coal combustion, traffic exhaust, biomass burning, soil dust, and construction dust emissions. The low nitrate: sulfate ratio suggested that stationary emissions were more important than vehicle emissions. The reconstructed masses of ammonium sulfate, ammonium nitrate, particulate carbonaceous matter, and fine soil accounted for 79% of the total measured PM2.5 mass; they also accounted for 92% of the total measured particle scattering.     

The Interannual Variation of Transboundary Contributions from Chinese Emissions of PM_(2.5) to South Korea

In recent years,several studies pointed out that anthropogenic emission sources in China which significantly contribute to the PM_2.5mass burden was an important cause of particulate pollution in South Korea.However,most studies generally focused upon a single pollution event.It is rare to see comprehensive research that captures those features prone to interannual variations concerning the transboundary pollutant contribution in South Korea using a unified method.In this paper,we establish the emission inventories covering East Asia in 2010,2015,and 2017,and then conduct the source apportionment by applying a coupled regional air quality model called the Integrated Source Apportionment Module(ISAM).Comparison of simulated and observed PM_2.5mass concentration at 165 CNEMC(China National Environmental Monitoring Center)sites suggests that the PM_2.5concentrations are well represented by the modeling system.The model is used to quantitatively investigate the contribution from emission sources in China to PM_2.5concentrations over South Korea and those features found to be prone to interannual variations are then discussed.The results show that the average annual contribution of PM_2.5has dropped significantly from 28.0%in 2010 to 15.7%in 2017,which strongly suggests that China has achieved remarkable results in the treatment of atmospheric particulates.     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 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 PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 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 PM_2.5 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 PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 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 PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.     

基于卫星遥感和地面观测资料的汾渭平原一次空气污染过程分析

利用MODIS和CALIPSO卫星资料、地面空气质量监测资料和地面气象要素资料,分析了汾渭平原2018年11月26日—12月3日持续性的重空气污染过程的形成、特征及污染物的可能来源。结果表明:此次污染过程中汾渭平原以中度以上污染为主,首要污染物为PM2.5和PM10;11个代表城市在11月20日—12月7日期间AQI连续超过100的天数除吕梁外均达到或超过10 d,西安、咸阳和渭南污染持续天数和严重污染天数均最多;污染发生时,地面至3 km以内的AOD与总AOD柱的比值为81%,沙漠沙尘和污染沙尘气溶胶出现频率最高,分别为60.18%和25.72%;26日12时BT左右沙尘自西向东传输,受秦岭的阻挡作用,同时低层以偏东风或者静风为主,大气静稳,无明显冷空气活动和降水产生,静稳和高湿的天气持续以及偏东风的阻挡和传输使得该次过程以沙尘和霾混合为主。     

Carbonaceous and inorganic species in PM<Subscript>10</Subscript> during wintertime over Giridih,Jharkhand (India)

Ambient concentrations of organic carbon (OC), elemental carbon (EC) and water soluble inorganic ionic components (WSIC) of PM₁₀ were studied at Giridih, Jharkhand, a sub-urban site near the Indo Gangatic Plain (IGP) of India during two consecutive winter seasons (November 2011–February 2012 and November 2012–February 2013). The abundance of carbonaceous and water soluble inorganic species of PM₁₀ was recorded at the study site of Giridih. During winter 2011–12, the average concentrations of PM₁₀, OC, EC and WSIC were 180.2?±?46.4; 37.2?±?6.2; 15.2?±?5.4 and 18.0?±?5.1 μg m^?3, respectively. Similar concentrations of PM₁₀, OC, EC and WSIC were also recorded during winter 2012–13. In the present case, a positive linear trend is observed between OC and EC at sampling site of Giridih indicates the coal burning, as well as dispersed coal powder and vehicular emissions may be the source of carbonaceous aerosols. The principal components analysis (PCA) also identifies the contribution of coal burning? +?soil dust, vehicular emissions?+?biomass burning and seconday aerosol to PM₁₀ mass concentration at the study site. Backward trajectoy and potential source contributing function (PSCF) analysis indicated that the aerosols being transported to Giridih from upwind IGP (Punjab, Haryana, Uttar Pradesh and Bihar) and surrounding region.