Analysis of mass concentration of atmospheric particulate matter in a sandstorm course and its affecting factors in the Taklimakan Desert

During the course of a major sandstorm from April 17 to April 23, 2008 in the Taklimakan Desert, data pertaining to the mass concentrations of different-sized atmospheric particulate matter were observed continuously with Grimm 1.108, Thermo RP 1400a, TSP, and CAWS-600 instruments. The results showed that： （1） during the entire sandstorm process there were some dif- ferences between the daily mean particle concentration peaks and the hourly mean particle concentration peaks because the actual sandstorm lasted for only about 4 hr, whereas more particles were accumulated in the floating dust days before and after the actual sandstorm; （2） the intensity of the sandstorm was enhanced with the increase of wind speed, and this was related to the peak mass concentrations of atmospheric particulate matter; the wind speed directly affected the concentration of atmospheric particulate matter： the higher the wind speed, the higher the mass concentration （〉0.23 μm was 39,496.5 μg/m^3, and 〉20.0 μm was 5,390.7μg/m^3）; （3） the concentration changes of PM10 and TSP were also related to the course and intensity of the sandstorm; and （4） the mass concentration of atmospheric particulate matter had the following sequence during the dust weather： clear day 〈 floating dust 〈 floating and blowing dust 〈 sandstorm. Temperature, relative humidity, and barometric pressure are important factors affecting the strength of storms, which could also indirectly affect the concentration change of atmospheric particulate matter.

Determination of brominated diphenyl ethers in atmospheric particulate matter using selective pressurized liquid extraction and gas chromatography–mass spectrometry with a negative chemical ionization

This study describes the development and validation of a sensitive and reliable method for determination of polybrominated diphenyl ethers(PBDEs)in atmospheric particulate matter using selective pressurized liquid extraction(SPLE)and gas chromatography–mass spectrometry with a negative chemical ionization(GC-NCI-MS).Extraction and clean-up were performed using PLE with 2 g florisil and 3 g silica placed in the extraction cells.Under optimal conditions,14 PBDEs were extracted at 70°C using hexane/dichloromethane(50:50,v/v)as solvent.Validation of SPLE returned excellent recoveries for most analytes,with relative standard deviations mostly below20%.Method detection limits ranged from 0.13 to15.38 ngám L^(-1)for the GC-MS analyses.The method was successfully applied to atmospheric particulate matter of Beijing,where analytes were detected in the range of182.79 to 468.99 pgám^(-3).

Concentrations and isotopic characteristics of atmospheric reactive nitrogen around typical sources in Beijing,China

With rapid economic growth in China, anthropogenic reactive nitrogen （Nr） emissions have more than doubled over the last two or three decades. Atmospheric Nr pollution is an environmental concern in China especially in megacities such as Beijing. In order to identify the impact of emission sources on atmospheric Nr pollution, we measured atmospheric Nr concentrations and their isotopic composition （δ15N） dynamics at three typical sites： landfill, pig farm and road traffic sites in Beijing from April 2010 to March 2011. Passive samplers were used for monitoring ammonia （NH3） and nitrogen dioxide （NO2）, two major Nr species, while their δ15N values were measured by a diffusion method combined with mass spectrometer approach. The raw water pool of the landfill and fattening house of the pig farm were important NH3 sources with mean NH3 concentrations being 2,829 and 2,369 μg/m3, respectively, while the road traffic site was a minor NH3 source （10.6 μg/m3）. NH3 concentrations at sites besides the landfill and roads were high in summer and low in winter due to the annual variation of temperature and the change of emission source intensity. In contrast, the NH3 concentrations inside the pig farm house were high in winter and low in summer, for the barn windows were open in summer and closed in winter. The mean NO2 concentrations were 89.8, 32.9 and 23.0 μg/m3 at the road traffic, the landfill and pig farm sites, respectively. Due to vehicle fuel combustion, NO2 concentration at the road traffic was the highest among the three sources, and the road traffic was a main NO2 emission source. PM10, pNH4＊ and pNO3- concentrations in particulate matter were higher in summer than in winter （except PM10 for the pig farm）. The δ15NH3 values ranged from -19.14‰ to 7.82‰, with an average of-0.05‰ for the landfill site, and the lowest values were observed in June and July. The δ15NH3 values for the pig farm site ranged from -29.78‰ to-14.05‰ with an average of-24.51‰, and the 515NH3 values were more negative in summer than in the other seasons. The （515NO2 values were -9.63%o to 7.04‰ with an average of -3.72%0 for the road traffic site. The δ15NO2 values were more negative in summer than those in the other seasons. The different δ15N values for the various Nr species in different sources may serve as important indicators for identifying atmospheric Nr sources in megacities. The results may also provide the theoretical basis for research on the atmospheric N deposition and its sources.

Analysis of Sources of Atmospheric Fine Particulates in Nan'ao County

Based on on-line single particle aerosol mass spectrometry （SPAMS） with high time resolution, the sources of atmospheric fine particu- late matter in Nan＇ao County were analyzed. The results showed that during the monitoring period from March 24 to 27 in 2015, the primary source of fine particulate matter in Nao＇ao County was motor vehicle exhaust, that is, 24.7% of fine particulates were from motor vehicle exhaust, followed by biomass burning （17.2%）, fire coal （17.2%）, and sea salt （13.3%）. The proportions of fire coal and sea salt revealed the peculiarity of sources of atmospheric fine particulate matter in Nan＇ao County. Therefore, it is suggested that some measures should be adopted to limit tourist traffic to reduce the adverse impact of motor vehicle exhaust on ambient air quality in Nan＇ao County.

High-Energy Atmospheric Physics: Ball Lightning

This article proposes an explanation for High-Energy Atmospheric phenomena through the frames of Hypersphere World-Universe Model (WUM). In WUM, Terrestrial Gamma-Ray Flashes (TGFs) are, in fact, Gamma-Ray Bursts (GRBs). The spectra of TGFs at very high energies are explained by Dark Matter particles annihilation in Geocorona. Lightning initiation problem is solved by GRBs that slam into thunderclouds and carve a conductive path through a thunderstorm. We introduce Multiworld consisting of Macro-World, Large-World, Small-World, and Micro-World, characterized by suggested Gravitational, Extremely-Weak, Super-Weak, and Weak interaction respectively. We propose a new model of Ball Lightning formation based on the Dark Matter Core surrounded by electron-positron plasma in the Small-World.

Concentrations,sources,and influential factors of water-soluble ions of atmospheric particles in Dunhuang Mogao Grottoes,a world heritage site in China

Atmospheric particle pollution is one of the major factors leading to degradation of ancient wall paintings,particularly heritage sites in arid and semi-arid regions.However,current systematic research on the changes,sources,and influential factors of atmospheric particulate matter and its water-soluble ion concentrations is not sufficient.Thus,the major water-soluble ion concentrations,sources,and influential factors of atmospheric particles PM_(2.5) and PM_(10)(particulate matter with an aerodynamic equivalent diameter≤2.5 and 10.0μm,respectively,in ambient air)were collected from Cave 16 and its ambient exterior environment in the Dunhuang Mogao Grottoes,China,between April 2015 and March 2016.Results showed that the concentrations of PM_(2.5) and PM_(10) inside and outside the cave were the highest in March 2016 and the lowest in December 2015.The higher particle concentration from March to May was related to the frequent occurrence of sand and dust events,and the lower particle concentration from June to September was associated with good diffusion conditions,increased precipitation,and an established cave shelterbelt.The concentration of particulate matter inside the cave was affected by the concentration of particles in the air outside the cave.Ca2+,NH+4,Na+,Cl-,and SO2-4were the main components of the total ions of PM_(2.5) and PM_(10) both inside and outside the cave.The total ions inside the cave were frequently affected by the disturbance of tourists'activities during the peak tourist season from May to August.Under the influence of dust,the total concentrations of Cl-,SO2-4,Na+,NH+4,and Ca2+in particles of different sizes inside and outside the cave increased,and the concentrations of Cl-,SO2-4,Na+,and Ca2+decreased during precipitation period.Backward air mass trajectory analysis suggested that the pollutants were mainly from Xinjiang,China.The pollutant sources of air particulates are straw burning,secondary pollution sources,soil dust,dry spring rivers,and tourist activities.

Magnetic Properties of Tree Leaves and Their Significance in Atmospheric Particle Pollution in Linfen City,China

Fifty-one tree leaves were sampled in the industrial area,residential area,and Fenhe River ecological zone,for the purpose of a magnetic study on atmospheric pollution in Linfen City,Shanxi Province,China.Measurements of mass-specific magnetic susceptibility(χ) show a significant variation range(from 11.6 × 10-8 m3/kg to 129.7 × 10-8 m3/kg).Overall values of magnetic susceptibility decline in the following sequence:industrial area > residential area > Fenhe River ecological zone.The relatively elevated concentration-related magnetic parameters(saturation isothermal remanent magnetization,anhysteretic remanent magnetization and magnetic susceptibility) appear in the industrial area,with their highest values in the vicinity of Linfen Steel Mill.Magnetic particles are dominated by multidomain,magnetite-like minerals.Magnetic particle concentration and grain size both decrease with the increasing distance from industrial area,indicating the industrial area,especially Linfen Steel Mill,is the main source of atmospheric particle pollution.Residential area and Fenhe River ecological zone are also affected by industrial emission to a certain extent.The results of this study indicate that magnetic measurements of tree leaves are practicable for monitoring and determination of atmospheric pollution in Linfen City.

Determination of Solar Radius and Earth’s Radius by Relativistic Matter Wave

In recent years, relativistic matter waves have been applied to the solar system to explain some quantum gravity effects. This paper shows that the solar size and Earth’s size are the consequences of Bode’s rule in terms of the relativistic matter wave. The solar radius is determined as 7e+8 (m) with a relative error of 0.72%;the Earth’s radius is determined as 6.4328e+6 (m) with a relative error of 0.86%. The Earth’s atmospheric circulation is also investigated in terms of the relativistic matter wave, the wind fields on the Earth’s surface are calculated, and the results agree well with experimental observation. These findings indicate that the solar system is under the control of the planetary relativistic matter waves.

Evaluation of Atmospheric Correction Algorithms for Landsat-8 OLI and MODIS-Aqua to Study Sediment Dynamics in the Northern Gulf of Mexico

Suspended particulate matter (SPM) is regarded as an energy source and a water quality indicator in coastal and marine ecosystems. To estimate SPM from ocean color sensors and land observing satellites, an accurate and robust atmospheric correction must be done. We evaluated the capabilities of ocean color and land observing satellite for estimation of SPM concentrations over Louisiana continental shelf in the northern Gulf of Mexico, using the Operational Land Imager (OLI) on Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua. In high turbidity waters, the traditional atmospheric correction algorithms based on near-infrared (NIR) bands underestimate SPM concentrations due to the inaccurate removal of the aerosol contribution to the top of atmosphere signals. Therefore, atmospheric correction in high turbidity waters is a challenge. Four atmospheric correction algorithms were implemented on remote sensing reflectance (Rrs) values to select suitable atmospheric correction algorithms for each sensor in our study area. We evaluated short-wave infrared (SWIR) and NIR atmospheric correction algorithms on Rrs products from Landsat-8 OLI and Management Unit of the North Sea Mathematical Models (MUMM) and SWIR.NIR atmospheric correction algorithms on Rrs products from MODIS-Aqua. SPM was retrieved from a band-ratio SPM-retrieval algorithm for each sensor. Our results indicated that SWIR atmospheric correction algorithm was the suitable algorithm for Landsat-8 OLI and SWIR.NIR atmospheric correction algorithm outperformed MUMM algorithm for MODIS.

Trace Metals Concentrations at the Atmosphere Particulate Matters in the Southeast Asian Mega City (Dhaka, Bangladesh)

Atmospheric particulate matters were collected on quartz fibre filters for 24 hours with a low volume sampler from January 2014 to March 2014 at the Southeast Asian mega city (Dhaka, Bangladesh). Particulate matters samples were analysed for eleven trace metals with inductively coupled plasma mass spectrometer (ICP-MS) at Cà Foscari University of Venice, Italy. Trace metals were extracted from filters with digestion method using a mixture of HNO3 and H2O2. The average concentration of the determined trace metals of As, Cd, Ni, Cu, Pb, Cr, Fe, Mn, Zn, Sband Se were 3.06, 6.28, 3.77, 11.98, 305.6, 9.2, 2057.0, 42.2, 303.3, 5.47 and 2.43 ng&#183m&#453, respectively. Arsenic concentration is much lower in the atmosphere of Dhaka, though Bangladesh has severe arsenic problem in the ground water. Lead and cadmium concentrations showed decreasing trend in Dhaka compared than previous measurements—but still they have very high levels compared than Europe and USA. There is very limited information for Mn, Sb and Se concentrations in Dhaka air. Correlation studies showed that several trace metals had potential joint sources of origin, e.g., manganese is highly correlated with iron (r2 = 0.97) and nickel (r2 = 0.84), copper (r2 = 0.86);lead with arsenic (r2 = 0.79) and antimony (r2 = 0.78). Enrichment factors analysis was also done with the data base for the respective metals in earth crust and coal fly ash. As and Cu both have combined sources, whereas Cd, Pb and Zn were from coal fly ash.Trace metals concentrations in Dhaka city air were much higher than Europe and USA but comparable or slightly lower than other south Asian countries. This is the first extensive study for the eleven trace metals with ICP-MS in Dhaka, Bangladesh.

“Smart” Surveillance of Dusty Behavior: Illuminating the Relationship between Particulate Matter and the Atmosphere

Although large amounts of research have been completed to find the relationship between particulate matter and climate change, they have still proven to be inadequate. Efforts to lay the foundations for understanding atmospheric chemical reactions have been repeatedly foiled by both the size and complexity of the task, which require more than the effort of a handful of researchers. Since the development of advanced physical models for dust behavior is projected to take years, what if laypeople could dramatically expedite this process by using their mobile devices as measurement tools? With relatively little effort by many individuals, previously unknown information about the earth’s atmosphere may at last become accessible thanks to recent advances in artificial intelligence. However, there are potential obstacles. Even if all technical problems are resolved, viable plans for battling particulate matter pollution will likely need to be accompanied by environmental policies. While technological breakthroughs give reason to hope for a brighter future, the resolution of global issues requires both grassroots changes and global efforts.

城市大气颗粒物中锑污染研究进展

随着工业化和城市化发展,高强度人类活动及锑化合物的广泛使用使城市大气环境中锑污染日趋严重。进入大气中的锑能长时间驻留并随大气环流进行长距离迁移造成跨区域污染。鉴于锑对人体的潜在毒性及致癌性,城市大气环境锑污染引起学术界和国家相关部门的高度重视,然而目前国内关于大气环境中锑的研究仍处于初期阶段。对城市大气颗粒物中锑的来源、污染特征、源解析等方面进行综述,在此基础上对大气环境中锑污染来源、迁移转化过程研究中的锑同位素应用前景进行展望,为进一步开展城市大气颗粒物锑污染研究、防治和环境管理提供参考。

我国6个典型城市大气能见度及其影响因素研究

采用线性相关性分析、分类变量分析等统计学方法,分析了巴彦淖尔、石家庄、廊坊、郑州、武汉、广州六市2019—2020年的PM_(2.5)与气象观测数据,研究了PM_(2.5)浓度与大气相对湿度对大气能见度的影响。结果表明:六市大气能见度年变化规律虽存在较大差异,但最低值均出现于每年12月—次年2月,且年变化规律基本一致;气象条件、相对湿度、PM_(2.5)浓度对能见度的影响明显,其中相对湿度通过改变PM_(2.5)物化性质间接影响能见度,与能见度相关程度相对较弱。PM_(2.5)浓度与能见度的线性相关性良好,以幂函数为主;整体上,相对湿度与PM_(2.5)浓度对大气能见度影响呈协同作用,相对湿度越大的城市对PM_(2.5)的控制要求越高。此外,PM_(2.5)浓度高于平台点时,大气能见度基本不随PM_(2.5)浓度增加而继续降低,只有PM_(2.5)浓度低于突变点时,大气能见度才会随PM_(2.5)浓度降低而显著提升,各市能见度突变点与平台期点所对应PM_(2.5)浓度差异较大。

莫高窟文物保存环境的大气颗粒物背景浓度及化学组成

大气颗粒物是潜在威胁遗址与文物的一种大气污染物,颗粒物沉降或吸附后覆盖文物表面细节,降低其审美价值,并带来进一步的物理或化学侵蚀。通过分析莫高窟开放洞窟(16窟、257窟)、非开放洞窟(320洞窟)和窟外大气中各粒径颗粒物(总悬浮颗粒物TSP、粗颗粒物PM_(10)和细颗粒物PM_(2.5))背景和典型沙尘天气质量浓度及其碳组分和水溶性无机离子组分含量,获得文物保存环境中大气颗粒物的质量浓度及化学组成。各观测季节内,非沙尘天气窟内TSP质量浓度介于48.4~60.0μg/m^(3),PM_(10)质量浓度介于13.3~61.3μg/m~3,PM_(2.5)质量浓度介于9.9~59.2μg/m^(3)。洞窟是否向公众开放对窟内颗粒物浓度水平和组成的影响不显著,开放和非开放洞窟颗粒物质量浓度的I/O比值多小于1,显示窟内颗粒物主要源于室外。窟内颗粒物化学组成中,地壳源矿物尘多占据主导地位,在沙尘频发的春季占比介于53.0%至80.7%之间,冬季占比介于17.1%~44.0%。其他化学组分中,细颗粒PM_(2.5)中碳组分和总水溶性无机离子含量占比明显高于TSP和PM_(10)。冬季窟内PM_(2.5)质量浓度低于春季,但碳组分和无机离子浓度值和含量占比均高于春季(除去春季16洞窟),冬季碳组分和无机离子含量占比高达60%,其中酸性组分含量占比和可达30%。对莫高窟大气颗粒物的控制不能忽视细颗粒浓度及其化学组成的潜在危害。

同位素结合PMF模型解析珠三角PM_(2.5)来源研究

二次气溶胶是大气细颗粒物(PM_(2.5))中最多的组分,客观识别其来源是PM_(2.5)源解析的难点,也是精确控制PM_(2.5)污染来源的关键。本研究在广东省鹤山超级大气监测站采集了76个PM_(2.5)样品,分析了其碳质组分(元素碳和有机碳)、水溶性离子(SO_(4)^(2-)、NH4^(+)、K^(+)、Ca^(2+)、Cl^(-)、Na^(+)、Mg^(2+)、NO_(2)^(-)和NO_(3)^(-))和金属元素(Fe、Cr、Cu、Mn、Ni、Pb、V、Zn、Cd、As)共20种化学组分,测定了7个PM_(2.5)代表样品的总碳(TC)放射性碳(^(14)C)。基于PM_(2.5)化学组分的PMF模型结果显示,生物质燃烧、海盐、土壤扬尘、轮船排放、工业过程、燃煤源和二次气溶胶分别贡献PM_(2.5)的18.98%、4.32%、13.85%、7.61%、14.08%、12.72%和30.03%。基于已发表的δ^(15)N(NO_(3)^(-))、δ^(18)O(NO_(3)^(-))结果,利用贝叶斯模型定量解析了NO_(3)^(-)的来源,并应用线型回归将PMF模型解析的二次气溶胶源再分配给一次颗粒源,结果显示,燃煤源(36.50%)、生物燃料源(29.35%)、土壤扬尘+海盐源(21.00%)和移动源(13.15%)是珠三角PM_(2.5)的主要来源。二次分配后PMF模型结果中TC的非化石源贡献与基于^(14)C结果的相对误差小于9%,说明PMF模型能很好地捕获PM_(2.5)主要贡献源,并且较准确地源解析珠三角的PM_(2.5),研究结果可为区域污染防治政策措施的制定提供科学依据。

电感耦合等离子体质谱分析大气颗粒中重金属离子含量的不确定度评定

评定了电感耦合等离子体质谱法测定大气颗粒物中重金属离子镉和铅含量的不确定度。建立了微波消解-电感耦合等离子体质谱对PM_(10)中重金属离子含量测试的数学模型,对影响测试过程的各个要素进行了分析,讨论了各不确定度分量,包括测量重复性、溶液定容、标准工作曲线拟合、标准物质、称量和仪器稳定性等,并开展了不确定度合成计算和扩展不确定度计算。结果表明,当大气颗粒物样品中镉和铅的质量浓度测量值分别为0.026、0.251μg/m^(3)时,扩展不确定度分别为0.000462、0.0036μg/m^(3)(k=2)。该方法可为建立大气颗粒物中重金属离子的分析和评价方法提供参考依据。

南京大气颗粒物化学组分的粒径分布和来源解析

大气颗粒物中化学组分的粒径分布与其来源、形成过程、环境及健康效应密切相关。而过去对不同季节颗粒物的粒径分布特征,以及不同来源对粗、细颗粒物的贡献的研究相对较少。于2022年12月(冬季)和2023年8月(夏季)在南京采集了大气分粒径颗粒物样品,分析了粗颗粒物(PM_(2.1-10))和细颗粒物(PM_(2.1))中碳质组分和主要水溶性无机离子的粒径分布和季节变化,运用正定矩阵因子分解模型(Positive Matrix Factorization,PMF)进行PM_(2.1-10)和PM_(2.1)的源解析。结果表明,在粒径分布特征上,冬夏两季有机碳(OC)、元素碳(EC)、水溶性有机碳(WSOC)的平均浓度呈双峰型分布。SO_(4)^(2-)和NO_(3)^(-)的季节平均浓度均为双峰型分布。NH_(4)^(+)主要分布在细颗粒物中,季节平均浓度呈单峰型分布,冬夏季均在0.43-0.65μm出现峰值。在季节变化上,颗粒物中除Na^(+)和SO_(4)^(2-)外的主要化学组分浓度均在冬季高于夏季。冬夏两季Ca^(2+)、Mg^(2+)主要集中在粗颗粒物中。根据PMF模型解析结果,南京大气颗粒物主要有4类来源贡献,即交通源、二次生成、生物质燃烧和扬尘源。PM_(2.1)主要来自二次生成和生物质燃烧源,冬夏季分别贡献了65.7%和61.0%,其中冬季生物质燃烧和二次硝酸盐的贡献占主导地位,而夏季主要来自二次硫酸盐的贡献。冬季PM_(2.1-10)主要来自交通源(41.8%),夏季则主要来自生物质燃烧和硝酸盐的二次生成贡献(43.9%)。研究探讨了大气颗粒物的化学组分的粒径分布特征、季节差异及来源,可为制定有针对性的大气污染防控措施提供科学依据。

大气颗粒物重金属污染排放浓度及环保检测技术研究

为降低大气颗粒物中重金属污染检测的检测误差,针对大气颗粒物重金属污染排放浓度及环保检测技术进行研究。利用光纤激光器对向污染的气体中发射一定波长的光束,等待污染分子完成光纤吸收后,获得红外吸收光谱,再分析分子运动状态,提取光谱中包含的特征。获取大气中声波传输信号,并结合声传播波动方程,计算出重金属污染排放浓度。最后,依托于稳态工况法和标准污染物排放限值,得出环保检测结果。实验结果表明:所提技术的检测结果的相对误差保持在3%以下,可以准确反映大气重金属污染情况。

济南市钢铁集聚区大气细颗粒物中碳组分污染特征

为分析钢铁集聚区大气细颗粒物(PM_(2.5))中碳组分的污染特征,对济南市钢铁集聚区和市区秋季(2020年10月15日至2020年10月24日)、冬季(2020年12月18日至2021年1月7日)和春季(2021年4月23日至5月2日)环境空气中PM_(2.5)进行手工采样,利用热光碳分析仪测定了PM_(2.5)中有机碳(OC)和元素碳(EC)的含量.结果表明,钢铁集聚区秋季OC和EC质量浓度范围分别为5.79—12.56μg·m^(−3)和1.34—3.44μg·m^(−3);冬季OC和EC质量浓度范围分别为3.92—55.54μg·m^(−3)和0.38—11.39μg·m^(−3);春季OC和EC质量浓度范围分别为2.14—4.70μg·m^(−3)和0.19—1.33μg·m^(−3),呈现显著的季节变化,表现为冬季>秋季>春季.钢铁集聚区冬季PM_(2.5)中OC和EC占比最高,分别为28.11%和5.36%,春季OC和EC占比最低,分别为9.82%和1.76%.钢铁集聚区秋季和冬季OC(EC)质量浓度均高于市区,分别是市区的2.12(2.68)、2.27(4.27)倍,表明钢铁集聚区秋冬季PM_(2.5)的污染状况比较严峻.在以PM_(2.5)为首要污染物的不同污染等级下,均为碳组分OC4和EC1的占比最高,分别占PM_(2.5)的9.0%和7.5%,是碳组分的主要贡献组分.钢铁集聚区春季、秋季和冬季SOC的浓度分别为1.09、1.79、10.80μg·m^(−3),分别占OC质量浓度的35.39%、19.02%和37.00%,表明钢铁集聚区冬季比其他季节二次有机污染较严重.由因子分析可知,钢铁集聚区碳组分主要来源于钢铁工业烧结等工序燃煤和柴油车尾气排放.研究成果为济南市钢铁集聚区周围环境空气质量改善措施的制定提供技术支撑.

Quantification of perfluorinated compounds in atmospheric particulate shows potential connection with environmental event

A method of quantification of perfluorinated compounds(PFCs)from atmospheric particulate matter(APM)is described.A single step pretreatment method,selective pressurized liquid extraction(SPLE),was developed to reduce the high matrix background and avoid contamination from commonly used multiple sample pretreatment steps.An effective sorbent was selected to purify the PFCs during SPLE,followed by liquid chromatography-tandem mass spectrometry(LC–MS/MS),for quantification of PFCs.Conditions affecting the SPLE efficiency,including temperature,static extraction time,and number of extraction cycles used,were studied.The optimum conditions were found to be 120℃,10 min,and 3 cycles,respectively.LC-MS/MS method was developed to obtain the optimal sensitivity specific to PFCs.The method detection limits(MDLs)were 0.006 to 0.48 ng/g for the PFCs studied and the linear response range was from 0.1 to 100 ng/g.To ensure accurate values were obtained,each step of the experiment was evaluated and controlled to prevent contamination.The optimized method was tested by performing spiking experiments in natural particulate matter matrices and good rates of recovery and reproducibility were obtained for all target compounds.Finally,the method was successfully used to measure 16 PFCs in the APM samples collected in Beijing over five years from 2015 to 2019.It is observed that some PFCs follow the trend of total PFC changes,and can be attributed to the environment influencing events and policy enforcement,while others don't seem to change as much with time of the year or from year to year.