2020年2月南宁市一次大气PM2.5污染成因分析

2020年1月31—2月2日新冠肺炎疫情期间,广西发生的一次区域性大气PM_2.5污染引发社会关注.以南宁市为例,利用在线气体组分及气溶胶监测系统（MARGA）、颗粒物激光雷达,结合地面气态污染物和气象数据卫星火点和后向轨迹等分析本次PM_2.5污染成因.依据空气质量分指数,将观测过程划分为优、良和污染3个时段.结果表明,污染时段与生物质焚烧相关的K⁺、Cl^-明显升高,K⁺、Cl^-平均浓度分别为优时段的3.6和17.0倍.3个时段8种水溶性离子总浓度占PM_2.5均在30%左右,3种二次水溶性离子浓度之和占8种离子总浓度的比例为83.33%~89.18%,二次无机组分占比高,与秸秆焚烧促进二次转化有关.二次水溶性离子浓度变化趋势与占比不一致,除了与秸秆燃烧排放特征有关,还与不同二次无机离子形成的机制及主要影响因素不同有关.秸秆焚烧火点集中分布在良时段的南宁市及周边城市,良时段秸秆露天焚烧直接排放大量颗粒物、气态污染物等,在污染时段边界层高度明显下降,湿度增加、静风等不利气象条件下积累,是造成疫情期间南宁市大气PM_2.5污染的主因.污染时段南宁市无明显的颗粒物垂直传输过程,近地面主要受到广东、广西北部湾偏南气流影响,区域污染传输小.     

古水稻土中多环芳烃的分布特征及其来源判定

测定了马家浜文化(距今约6 000a)遗址2个剖面表层土壤、古代水稻土和古代旱地土壤、以及底层土壤中15种多环芳烃的含量,并对其可能来源进行了判定.结果表明,表层土壤中PAHs的含量分别为202.9μg·kg^-1和207.7μg·kg^-1,主要来源于大气沉降;古水稻土中PAHs含量明显降低,仅为56.0μg·kg^-1,但高于古旱地土壤及底层土壤。古旱地土壤及底层土壤PAHs含量在32.0～36.9μg·kg^-1.古水稻土中,2环和3环所占比例较大,达63%,萘和菲含量最高,而4环以上的多环芳烃含量较低.Phe/Ant和BaA/Chr比值和有机质¹³C-NMR图谱显示,古水稻土中的多环芳烃主要来源于水稻秸秆的焚烧,同时还原条件下的生物合成可能是其另一个重要来源.     

计划烧除的应用与研究

火作为一个重要的生态因子影响着生态系统的平衡。林火生态是计划烧除的理论基础,讨论作广科学家应用于营林,生态系统的保护和野动物的保护等方面。文中还对林地计划火烧的间隔期和计划划烧除的效果与评价作了阐述,并讨论了计划烧除在应用在存在的问题。     

镁砂窑的黑烟治理

本文介绍了乡镇镁砂工业的主干装备———镁砂窑轻烧镁砂由燃煤改燃煤气的新工艺、煤的气化原理及反应顺序、镁砂窑改变燃料的比较计算、简易煤气发生炉的构造和煤气燃烧用的空气量计算等，并对镁砂窑采用煤气燃烧工艺后所产生的综合效果，作了简单的评价     

球团竖炉清洁生产工艺改造

球团竖炉生产使用散煤作为燃料，产生的烟尘和二氧化硫对环境造成严重污染，本文通过实际案例的研究，探索一种清洁能源，根治彻底长期困扰球团竖炉的污染环境问题，同时提高产品质量，使企业的发展走向良性循环清洁生产道路。     

炼山对杉木人工幼林养分流失影响的定量研究

根据５ａ长期定位观察结果,本文应用两模型参数ｔ检验、弹性分析及边际分析法,探讨年时间序列对炼山与对照的杉木人工幼林养分流失的效应。ｔ检验表明,不同处理在年时间序列上的铵态氮、亚硝态氮、硝态氮、磷酸盐、钾、有机质流失模型的Ｂ、Ａ参数存在显著差异。弹性分析和边际分析表明,年时间对不同处理的上述养分效应呈负效应,在炼山条件下,上述养分流失的弹性系数分别为－１．２１５％、－１．２１４％、－１．２１５％、－１．２１５％、－１．２４１％、－１．２１４％,上述养分流失的边际量分别为－０．３９４ｋｇ、－０．０３３ｋｇ、－０．３６５ｋｇ、－０．０２３ｋｇ、－３０．０１０ｋｇ、－５９．４２１ｋｇ。在不炼山处理下,上述养分流失的弹性系数分别为－０．８４２％、－０．８５１％、－０．８４４％、－０．８５４％、－０．８４５％、－０．８４１％,上述养分流失边际量分别为－０．１５９ｋｇ、－０．０１０ｋｇ、－０．０８５ｋｇ、－０．００６ｋｇ、－１２．０２４ｋｇ、－１７．７６７ｋｇ。     

Numerical simulation of smoke plumes from large oil fires

A large eddy simulation (LES) model of smoke plumes generated by large outdoor pool fires is presented. The plume is described in terms of steady-state convective transport by a uniform ambient wind of heated gases and particulate matter introduced into a stably stratified atmosphere by a continuously burning fire. The Navier-Stokes equations in the Boussinesq approximation are solved numerically with a constant eddy viscosity representing dissipation on length scales below the resolution limits of the calculation. The effective Reynolds number is high enough to permit direct simulation of the large-scale mixing over two to three orders of magnitude in length scale. Particulate matter, or any non-reacting combustion ;product, is represented by Lagrangian particles which are advected by the fire-induced flow field. Background atmospheric motion is described in terms of the angular fluctuation of the prevailing wind, and represented by random perturbations to the mean particle paths. Results of the model are compared with two sets of field experiments.     

Monitoring the transport of biomass burning emissions in South America

The atmospheric transport of biomass burning emissions in the South American and African continents is being monitored annually using a numerical simulation of air mass motions; we use a tracer transport capability developed within RAMS (Regional Atmospheric Modeling System) coupled to an emission model. Mass conservation equations are solved for carbon monoxide (CO) and particulate material (PM2.5). Source emissions of trace gases and particles associated with biomass burning activities in tropical forest, savanna and pasture have been parameterized and introduced into the model. The sources are distributed spatially and temporally and assimilated daily using the biomass burning locations detected by remote sensing. Advection effects (at grid scale) and turbulent transport (at sub-grid scale) are provided by the RAMS parameterizations. A sub-grid transport parameterization associated with moist deep and shallow convection, not explicitly resolved by the model due to its low spatial resolution, has also been introduced. Sinks associated with the process of wet and dry removal of aerosol particles and chemical transformation of gases are parameterized and introduced in the mass conservation equation. An operational system has been implemented which produces daily 48-h numerical simulations (including 24-h forecasts) of CO and PM2.5, in addition to traditional meteorological fields. The good prediction skills of the model are demonstrated by comparisons with time series of PM2.5 measured at the surface.     

HIPS阻燃复合材料三元潜在火灾危险性评价

将高抗冲聚苯乙烯树脂颗粒(纳米/微米级)、十溴二苯乙烷颗粒、三氧化二锑、弹性体、分散剂和偶联剂通过一步熔融共混工艺先行制备UL94 V-0级阻燃母粒,再将其与HIPS本体树脂按不同比例混合制得阻燃复合材料,并利用极限氧指数(LOI)、垂直燃烧(UL94)及ISO 5660锥形量热计三项测试表征制得样品的燃烧和火灾性能,从中提炼和分析LOI、垂直燃烧等级和最大热释放速率(Pk HRR)等三元关键指标相关性,给出了定性定量相结合的潜在火灾危险性分级范围。结果表明:UL94燃烧等级和Pk HRR相关性体现为当Pk HRR≤330.0 k W/m~2时,试样UL94等级均为V-0级;UL94燃烧等级和LOI相关性体现为随UL94燃烧等级从V-0降到HB时,试样LOI从27.0降到17.0;Pk HRR与LOI相关性体现为Pk HRR与LOI呈粗略反向线性相关性;UL94燃烧等级、Pk HRR和LOI三元相关性体现为当LOI22.0、Pk HRR为399.0~665.0 k W/m~2时,材料UL94燃烧等级介于HB~V-2。     

Observations of atmospheric pollutants at Lhasa during 2014–2015: Pollution status and the influence of meteorological factors

Atmospheric pollutants including SO₂, NO₂, CO, O₃ and inhalable particulate matter (PM_2.5 and PM₁₀) were monitored continuously from March 2014 to February 2015 to investigate characteristics of air pollution at Lhasa, Tibetan Plateau. Species exhibited similar seasonal variations except O₃, with the peaks in winter but low valleys in summer. The maximum O₃ concentration was observed in spring, followed by summer, autumn, and winter. The positive correlation between O₃ and PM₁₀ in spring indicated similar sources of them, and was assumed to be turbulent transport. Temperature was the dominant meteorological factor for most species in spring. High temperature accelerates O₃ photochemistry, and favors air disturbance which is conductive to dust resuspension in spring. Relative humidity (RH) and atmospheric pressure were the main meteorological factors in summer. RH showed negative correlations with species, while atmospheric pressure posed opposite situation. Wind speed (WS) was the dominant meteorological factor in autumn, the negative correlations between WS and species indicated diffusion by wind. Most species showed non-significant correlations with meteorological factors in winter, indicating the dependence of pollution on source emission rather than restriction by meteorology. Pollution weather character indicated that emissions were from biomass burning and dust suspension, and meteorological factors also played an important role. Air stream injection from the stratosphere was observed during O₃ pollution period. Air parcels from Southwest Asia were observed during air pollution period in winter. An enhancement in air pollutants such as O₃ would be expected in the future, more attention should be given to countermeasures for prevention of air pollution in the future.