桂林城区大气能见度与颗粒物浓度和气象因子关系研究

利用2015年1月至2017年6月桂林国家基本气象站能见度、相对湿度、气温、气压、降水等气象要素和PM₁₀、PM_2.5、PM_1.0颗粒物质量浓度资料,分析桂林城区大气能见度与颗粒物浓度和气象因子之间关系。结果表明：桂林城区大气能见度和PM₁₀、PM_2.5、PM_1.0呈对数关系,相关系数分别为-0.341、-0.461、-0.509,颗粒物对大气能见度影响在相对湿度为60%—70%时最为显著。在各气象因子中,大气能见度与风速的相关性最好,其次为相对湿度,与风速呈二次函数关系,与相对湿度呈幂指数关系,与温度相关性较小,与气压在秋冬季节呈正相关,相关系数冬季可达0.301,但在春、夏季节相关性不显著;利用颗粒物浓度和气象要素建立8种大气能见度非线性统计回归模型,比较后发现利用PM_1.0、风速、相对湿度、气温等因子建立的不同季节大气能见度拟合公式在实际检验中效果最优,能较好地模拟桂林地区大气能见度的变化。     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.     

风沙流中沙粒浓度分布的实验研究

利用粒子图像测速技术（PIV）,在风洞内对与天然沙接近的石英沙风沙流沙颗粒浓度沿高度分布进行了研究。对 3种不同轴线风速研究结果表明,风沙流中沙粒浓度沿水平方向基本不变,而随高度呈指数衰减,而且其衰减速率与风速密切相关。风速越大,衰减速率越慢;风速越小,衰减速率越快。风沙运动一旦发生时,靠近沙床表面的沙粒浓度随风速变化很小,可以认为趋于稳定,达到最大值。     

The tropospheric distribution of formaldehyde during TROPOZ II

A series of 149 measurements of the HCHO mixing ratio were made between 0 and 10 km altitude and 70° N to 60° S latitude during TROPOZ II. The data show a vertical decrease of the HCHO mixing ratio with altitude at all latitudes and a broad latitudinal maximum in the HCHO mixing ratio between 30° N and 30° S at all altitudes. The measured mixing ratios of HCHO are considerably higher than those expected from CH₄ oxidation alone, but agree broadly with the average latitude by altitude distribution of HCHO derived by a 2D model including emissions of C₁–C₇ hydrocarbons. A number of the regional scale deviations of the measured HCHO distribution from the average modelled one can be explained in terms of the local wind field.     

On the Association between Spring Arctic Sea Ice Concentration and Chinese Summer Rainfall： A Further Study

In our previous study,a statistical linkage between the spring Arctic sea ice concentration(SIC)and the succeeding Chinese summer rainfall during the period 1968–2005 was identified.This linkage is demonstrated by the leading singular value decomposition(SVD)that accounts for 19%of the co-variance.Both spring SIC and Chinese summer rainfall exhibit a coherent interannual variability and two apparent interdecadal variations that occurred in the late 1970s and the early 1990s.The combined impacts of both spri...     

Concentration profiles of particles settling in the neutral and stratified atmospheric boundary layer

An expression for the vertical equilibrium concentration profile of heavy particles, including the effects of canopy on the eddy diffusivity as well as corrections for atmospheric stability, is proposed. This expression is validated against measurements of vertical concentration profiles of corn pollen above a corn field. The fitted theoretical profiles show that particle settling is correctly accounted for. The sensitivity to variations in the turbulent Schmidt number, settling velocity and stability corrections are explicitly characterized. The importance of independent measurements of the surface flux of pollen in future experiments is noted.     

液态水含量和冰晶浓度对闪电频数影响的数值模拟研究

假定在软雹和冰晶碰撞的非感应起电机制为主要的起电机制成立的条件下，数值模拟研究了国际上公认的Fletcher和H—M冰晶产生机制以及云中的液态水含量对雷暴云放电过程（区分了云闪和地闪）的影响。结果表明，随着气压和温度的变化，在两种冰晶产生机制假定下，冰晶浓度分布有很大差异，这直接导致了雷暴云内电活动的差异。液态水含量的增加将使得首次放电时间延迟，同时将引起放电位置的下降和闪电频数的减少。     

营口市一氧化碳中毒事件发生日气象条件分析

利用近10 a营口市一氧化碳浓度监测资料和气象监测资料,分析了一氧化碳中毒事件发生与一氧化碳浓度的关系,探讨了一氧化碳中毒事件发生日的地面天气形势和局地气象条件特征。结果表明:一氧化碳中毒事件发生日空气中一氧化碳浓度值偏高;弱高压类、低压类和均压类天气形势均可能发生一氧化碳中毒事件;气压梯度小,风速小,气温变化小,不利于污染物扩散是造成一氧化碳中毒的主要原因。     

论边界层中的大气扩散PDF模式

基于大气扩散Ｋ理论，用作为风速脉动均方差和拉氏时间尺度函数的湍流交换系数，得到了直接利用风速脉动几率密度而不用扩散参数的大气扩散ＰＤＦ模式。分别研究了对流边界层上升气流区与下降区垂直速度的统计特征，求得双正态ＰＤＦ模式。在给定ＣＢＬ自身参数如对流特征速度ｗ＊，顶高ｈｉ和源高度上的平均风速时，该模式计算出的无量纲浓度分布与室内外测试结果一致。     

CO2浓度渐增对气温影响的敏感性试验

使用辐射对流模式，研究了中纬度冬季气温对于ＣＯ２浓度变化的敏感性。结果表明：气温变幅随ＣＯ２浓度渐增呈现先快后慢的非线性特征；气温变幅具有一定的稳定性。