Variation of particle number and mass concentration in various size ranges of ambient aerosols in Eastern Germany

There is an ongoing debate on the question which size fraction of particles in ambient air may be responsible for short-term responses of the respiratory system as observed in several epidemiological studies. However, the available data on ambient particle concentrations in various size ranges are not sufficient to answer this question.Therefore, on 180 days during the winter 1991/92 daily mean size distributions of ambient particles were determined in. Erfurt, a city in Eastern Germany. In the range 0.01–0.3 μm particles were classified by an electrical mobility analyzer and in the range 0.1–2.5 μm by an optical particle counter. From the derived size distributions, number and mass concentrations were calculated.The mean number concentration over this period of time was governed by particles smaller than 0.1 μm (72%), whereas the mean mass concentration was governed by particles in the size range 0.1–0.5 pm (83%). The contribution of particles larger than 0.5 μm to the overall number concentration was negligible and so was the contribution of particles smaller than 0.1 μm to the overall mass concentration. Furthermore, total number and mass concentrations in the range 0.01–2.5 μm were poorly correlated.The results suggest that particles larger than 2.5 μm (or even larger than 0.5 μm) are rare in the European urban environment so that the inhalation of these particles is probably not relevant for human health. Since particle number and mass concentrations can be considered poorly correlated variables, more insight into health-related aspects of particulate air pollution will be obtained by correlating respiratory responses with mass and number concentrations of ambient particles below 0.5 μm.     

Ambient air analysis round robin

A laboratory intercomparison study was carried out to determine the current capability of Canadian laboratories for the analysis of dioxins and furans in ambient air. Seven laboratories (government and private) participated in the analysis of exposed foam/filter samples, ambient air extracts and standard mixtures. The results indicated that a number of laboratories were capable of the aforementioned analyses; however, further analytical methodology development is also required.     

Reduction of sampling and analytical errors for electron microscopic analysis of atmospheric aerosols

Electron microscopy-energy dispersive spectroscopy (EM/EDS) can be used to determine the elemental composition of individual particles. However, the accuracy with which atmospheric particle compositions can be quantitatively determined is not well understood. In this work we explore sources of sampling and analytical bias and methods of reducing bias. Sulfuric acid [H₂SO₄] and ammonium sulfate [(NH₄)₂SO₄] particles were collected on beryllium, silicon, and carbon substrates with similar deposition densities. While [(NH₄)₂SO₄] particles were observed on all substrates, [H₂SO₄] and ammonia-treated [H₂SO₄] particles could not be found on beryllium substrates. Interactions between the substrate and sulfuric acid particles are implicated. When measured with EM/EDS, [H₂SO₄] particles exposed to ammonia overnight were found having lower beam damage rates (0.000 ± 0.002 fraction s⁻¹) than those without any treatment (0.023 ± 0.006 fraction s⁻¹) For laboratory-generated [C₁₀H₆(SO₃Na)₂] particles, the composition determined using the experimental k-factors evaluated from independent particle standards of similar composition and size shows an error less than 20% for all constituents, while greater than 78% errors were found when k-factors were calculated from the theory. This study suggests (1) that sulfate beam damage can be reduced by exposure of atmospheric particle samples to ammonia before analysis, (2) that beryllium is not a suitable substrate for atmospheric particle analysis, and (3) calibration (k-factor determination) using particle standards of similar size and composition to particles present in the atmosphere shows promise as a way of improving the accuracy of quantitative EM analysis.     

Modeling secondary organic aerosol formation from oxidation of α-pinene, β-pinene, and d-limonene

The biogenic species α-pinene, β-pinene, and d-limonene are among the most abundant monoterpenes emitted globally. They are also important precursors to secondary organic aerosol (SOA) formation in the atmosphere. This study involves the development of proposed oxidation mechanisms for these three species. Semi- and non-volatile oxidation products with the potential to lead to SOA formation are predicted explicitly. Simulation code that describes the gas-phase oxidation mechanisms including reactions that lead to ozone (O₃) formation is coupled to an equilibrium absorptive partitioning code. The coupled model is used to simulate both gas-phase chemistry and SOA formation associated with oxidation of these three species in chamber experiments involving single as well as multiple oxidants. For the partitioning model, required molecular properties of the oxidation products are taken from the literature or estimated based on structural characteristics. The predicted O₃ and SOA concentrations are typically within ±50% of measured values for most of the experiments except for the experiments with low initial hydrocarbon concentrations and the nitrate radical experiments with α-pinene. The developed model will be used to update a gas-phase chemical mechanism and a SOA formation module used in a three-dimensional air quality model.     

Source characterization and identification by real-time single particle mass spectrometry

A Real-Time Single Particle Mass Spectrometer, RSMS-3, was deployed to Wilmington, Delaware to study regional and local contributions to fine and ultra-fine urban particulate matter (PM). Approximately two-thirds of PM₁ consisted of internally mixed secondary aerosol. The remaining one-third was externally mixed including biomass burning (13%), fossil fuel combustion (7%) and various industrial sources (13%). In this last group, particle classes containing specific combinations of transition and/or heavy metals gave wind-rose plots consistent with specific point sources. For example, particles containing V and Ni were detected from different wind directions than those containing V and Fe. Samples from two industrial emission stacks, a steel manufacturing facility 10 km away and a coal-fired electrical power generation facility 5 km away, were analyzed and compared to the ambient data set. In each case, a direct correlation was found: a Pb–Zn–K–Na class for the steel manufacturing facility and an Fe–La/Ce class for the power generation facility. The ambient particle classes showed additional small signals from secondary components indicating atmospheric processing. Ambient particle classes containing only a subset of these elements, such as Zn only, Fe only and Pb–K only, were nonspecific, that is, the wind-rose plots were more diffuse and the particles could not be mapped to individual sources. The merits of stack sampling as an aid to interpreting single particle data sets are discussed.     

上海市路边环境空气黑碳气溶胶污染特征及影响因素研究

为研究上海市路边环境空气黑碳(BC)的污染特征,采用连续监测方法对2016年1月至2018年12月上海市路边环境空气BC浓度进行了监测,并同步监测了气象因子,分析了BC的时间变化特征,探讨了气象因素对BC的影响以及不同空气质量等级下BC浓度水平。结果表明:2016、2017、2018年上海市路边环境空气BC年均质量浓度分别为(2 908±2 189)、(2 959±2 224)、(2 824±2 002) ng/m3,呈现出下降趋势;2016、2017、2018年BC与PM2.5年均质量浓度比分别为9. 30%、9. 20%、9. 50%;BC季节变化特征明显,整体表现为春夏高、秋冬低的特点;昼夜变化特征均呈现出双峰分布,第一个峰值均出现在06:00,第二个峰值均出现在16:00-19:00,且第一个峰值高于第二个峰值。气象因素对BC有一定影响,在降水、相对湿度低以及非静风条件下BC浓度较低。随着上海市空气质量由好转差,上海市路边环境空气BC浓度均呈现上升趋势,空气质量为良、轻度污染、中度污染、重度污染时路边环境空气BC平均浓度分别较空气质量为优时增加了0. 38、0. 96、1. 61、1. 96倍。     

广州不同环境空气PM2.5中金属元素污染特征与风险评价

根据2015年广州城区磨碟沙、内陆郊区天湖和近海郊区万顷沙不同环境空气PM_2.5中金属元素（Pb、Cd、Cr、Ni、As等23种）监测数据，分析其污染特征与富集程度，并评估潜在生态风险和健康风险，为大气污染风险防控提供支持。结果显示：广州大气PM_2.5中金属K、Na、Fe、Ca、Al和Zn含量相对较高。总元素浓度总体呈冬季最高、夏季最低的特征，且随PM_2.5污染加重而升高，但总元素在PM_2.5中的占比下降。Cd、Se、Zn、Cu、Mo、Pb和Na富集严重（富集因子>100），体现了人类活动的重要影响，磨碟沙城区站富集因子通常高于另2个站点。广州大气总金属元素潜在生态危害程度为"很强"，Cd贡献为主，Pb、Cu和As元素贡献分别在天湖、磨碟沙和万顷沙位列第二。As、Cr和Mn是大气金属元素健康风险的主要贡献者；磨碟沙的总致癌效应风险高于万顷沙和天湖，但万顷沙的总非致癌效应风险最高。     

宜宾地区气溶胶垂直结构地基空基联合监测分析

利用Cloud-Aerosol LIDAR with Orthogonal Polarization （CALIOP）正交极化云-气溶胶星载激光雷达Level1B资料和LGJ-01型号气溶胶地基激光雷达资料对宜宾地区2016年12月—2017年2月无污染时期、少云轻度污染时期和多云重度污染时期气溶胶的衰减后向散射系数和退偏振比光学参数的垂直分布进行对比分析研究。结果表明：少云轻度污染时期，CALIOP数据监测到海拔高度为0.2~1.0 km范围内气溶胶颗粒集中分布，LGJ-01数据监测到厚度约为0.2 km的近地面气溶胶层，2个激光雷达监测结果基本一致；重度污染时期，LGJ-01地基激光雷达能够较好地探测近地面气溶胶层，CALIOP星载激光雷达能够较好地探测到高空云层，若将两者结合，则能实现不同天气状况下的综合探测，以期较全面客观地为研究气溶胶垂直结构提供观测及科研数据。     

Enumeration of Legionella pneumophila in cooling tower water systems

Legionella pneumophila, the causative agent of Legionnaires disease, is known to colonise and frequently grow in cooling tower waters. Disease is acquired by inhaling aerosol contaminated by legionellae. Determination of the count of Legionella pneumophila in cooling tower waters may, therefore, be useful for risk assessment. In our survey, 103 water samples from 50 cooling towers were examined over a five-year period to indicate the seasonal distribution and the ecology of L. pneumophila, as regards temperature and pH. L. pneumophila serogroup 1 was found in 44% of the isolated strains, which is primarily responsible for the majority of Legionnaires disease. The large majority of examined towers had levels of L. pneumophila in the high-risk category. These cooling towers have been linked to many outbreaks of Legionnaires disease.     

南京市环境空气中挥发性有机物的组成与特点

参照美国EPATO17的方法研究南京市不同功能区(交通区、商业旅游区、居住区、工业区和清洁对照点)环境空气中挥发性有机物(VOCs)在一年四季中的组成及浓度水平。共检出189种挥发性有机物,并随气温下降而减少;苯系物稳定存在于各功能区,浓度秋季最高。交通区污染最严重。