煤矿瓦斯浓度与气象因子相关分析及预报模型

对山西省大同市地方煤矿1979~1997年发生的90起重大典型事故案例进行分析,发现瓦斯事故是发生次数最多,占事故总数的33%,而其造成的灾害也最重。瓦斯浓度的高低与气象因子具有一定的相关性,通过统计计算,得出了旬瓦斯浓度与旬气温、旬气压的相关关系,建立了旬瓦斯浓度预报模型和逐日瓦斯浓度等级预报模型,预报拟合率和试报效果较好。利用该研究成果,结合中短期天气预报,可以提前预报瓦斯浓度的变化趋势,对于搞好煤矿安全生产的管理,及时加大通风,减少事故发生具有重要意义。     

区域空气质量数值预报系统CAPPS3在辽宁的应用

利用城市大气污染数值预报系统CAPPS的第三版(CAPPS3),经过安装、调试和本地化、自动化处理,建立起适合于辽宁的区域空气质量数值预报系统,用于预报辽宁的城市污染指数和等级以及各污染物的日均浓度分布.通过模式预报结果与监测资料的对比,发现辽宁14个主要城市SO2、NO2预报准确率的总体水平明显高于PM10.区域污染物浓度分布位置和大小的预报结果与实际情况相符,污染物小时浓度的演变也与实际风场的变化趋势保持一致,表明CAPPS3模式系统能够及时准确地预报出区域污染的形成和发展过程.     

新型扩散云室搭建及其对黄山地区大气冰核的观测研究

本研究利用自行搭建的大气冰核高压静电采样器和静力真空水汽扩散云室,并结合其他大气冰核及气象要素观测仪器,于2011年5～9月及2012年9～10月在黄山三层不同高度上同时进行大气冰核及相关气象要素的连续观测。结果显示:黄山地区总冰核数浓度平均为18.74 L-1,凝结冻结核化冰核数浓度平均为0.79 L-1,凝华核化冰核数浓度平均为0.19 L-1。黄山地区冰核数浓度,随着高度的增加而减小;且存在春季较高、秋季居中、夏季较少的季节变化规律;下午达到一天中的最高值,夜晚达到一天中的最低值;总冰核数浓度较北方少。黄山山顶冰核数浓度随活化温度的升高而减小,随过饱和度的升高而增大,随风速的增强而增大,长期主要由西南风向山顶的输送,且其主要由大粒子来充当。     

Quantitative Evaluation of Water Deposited By Dew on Monuments

Samples of White and Green Carrara marble, and three types oflimestone and brick exposed in the field vertically and horizontally were used to evaluate condensationon monuments during clear sky nights. Experiments in a simulation chamber under controlledconditions led to a general equation for the actual amount of water deposited on a surface by dew.This is determined by: How much and for how long the surface temperature falls below the dew point,the moisture content in the air and the ventilation. On clear nights, the condensation on buildingstructures facing the sky may reach some 0.2 kg m^-2 (or 0.2 mm), whereas condensation on verticalsurfaces is very small. Computation of the seasonal trend of night-time condensationshowed that the maximum amount of water condensed per night occurs in the autumn, with the moreabundant concentration of moisture in the air. The total amount of water condensed per month isfound to be a maximum in the summer-autumn period. Morning condensationfor the thermal inertia of monuments is also relevant, and has been calculated to reach the same order of magnitude as thenocturnal dew. A detailed analysis of the temperature and mixing ratio profiles near a condensingsurface has shown two different situations. In still air, the two profiles follow an exponentiallaw and the thermal and the concentration layers lie within a few tens of millimetres. Inthe presence of turbulence, the thickness of these two layers is dramatically reduced. In still air, infront of a vertical, chilly surface, the deposition rate of air pollutants by thermophoresis and/orStefan flow is increased by 3 or 4 times in comparison with a horizontal surface. In the presence ofturbulence, the thickness of the thermal and concentration layers was dramatically reduced, makingthese two kinds of deposition much faster.     

内蒙古东部春季三类沙尘天气气溶胶散射系数及其与PM10、能见度相关性分析

利用内蒙古东胜、锡林浩特两站2004~2006年春季（3~5月）积分浊度计的观测资料,结合同期PM10质量浓度、大气能见度等资料,分析了背景、扬沙、沙尘暴、强沙尘暴等不同强度沙尘天气气溶胶散射系数的分布特征,讨论了不同强度沙尘天气过程中散射系数、PM10、能见度的日变化规律,以及不同强度沙尘天气过程中散射系数与PM10质量浓度、散射系数与能见度的相关关系。结果表明:散射系数能够很好地反映沙尘天气强度;随沙尘天气强度增强,散射系数日变化从双峰型向单峰型转变;沙尘天气强度较弱时,PM10与散射系数的日变化不相似,强沙尘暴过程中PM10与散射系数的日变化有一定的相似性;能见度与散射系数日变化趋势相反;散射系数与PM10质量浓度呈正相关性,沙尘天气越强,相关性越好,背景、扬沙、沙尘暴、强沙尘暴相关系数分别为0.201、0.809、0.898和0.953;散射系数与能见度有指数相关关系,随沙尘天气强度增强二者相关性逐渐增强,背景、扬沙、沙尘暴、强沙尘暴相关系数分别为-0.773、-0.870、-0.918和-0.940。     

新疆天山山区大气冰核浓度的测量及分析

利用2001年6、7月份在新疆天山山区两个取样点取得的冰核资料，计算了山区中的冰核浓度，研究了冰核平均浓度日变化、日际变化的规律，并分析了天山山区冰核浓度与一些气象因子的关系及可能原因。得出以下结论：天山山区的大气冰核主要来源于地面土壤，比较缺乏；冰核浓度易受气象因子、地表状况的影响，日变化和日际变化明显．     

非常定自适应网格模式在台风路径数值预报中的应用

本文将作者在前文中介绍的非常定自适应网格模式用于台风路径的数值预报。由于自适应网格在台风中心附近安排了较密的网格，有效地提高了网格的分辨率，使得台风环流的结构在预报48小时以后仍能保持，其预报的路径与实况相比令人鼓舞。     

花粉浓度预报

重点探讨气候和植物对空气中花粉浓度的影响。通过对天津市河西区气象铁塔站、和平区南京路站1999年4月－2000年10月花粉观测资料分析表明：一年中花粉浓度有明显的周期性和季节性。经统计分析得出：当日花粉实况、气温日较差、日平均气温距平与未来25小时花浓度相关显著，用基作因子分别建立了春季、夏秋逐日花粉浓度预报主程，复相关系数分别为0．73和0．76，均通过F检验。同时利用降水、风、云量气象要素以及植物物候加以订正，作花粉浓度预报效果很好。     

用非色散红外气体分析仪进行大气CO2本底浓度的测量

按WMO关于开展全球CO2监测的要求，在对引进设备进行改进的情况下，建立了我国开展大气CO2本底浓度连续测量的红外气体分析测量系统及有关方法。系统的测量精度优于0.1ppm，完全满足全球本底测量的要求，并具有较好的国际可比性。在此基础上，首次取得了我国大陆上空大气CO2的本底浓度资料。     

Verifying Fossil-Fuel Carbon Dioxide Emissions Forecasted by an Artificial Neural Network with the GEOS-Chem Model

In this study, the authors developed an en- semble of Elman neural networks to forecast the spatial and temporal distribution of fossil-fuel emissions （ff） in 2009. The authors built and trained 29 Elman neural net- works based on the monthly average grid emission data （1979-2008） from different geographical regions. A three-dimensional global chemical transport model, God- dard Earth Observing System （GEOS）-Chem, was applied to verify the effectiveness of the networks. The results showed that the networks captured the annual increasing trend and interannual variation of ff well. The difference between the simulations with the original and predicted ff ranged from -1 ppmv to 1 ppmv globally. Meanwhile, the authors evaluated the observed and simulated north-south gradient of the atmospheric CO2 concentrations near the surface. The two simulated gradients appeared to have a similar changing pattern to the observations, with a slightly higher background CO2 concentration, - 1 ppmv. The results indicate that the Elman neural network is a useful tool for better understanding the spatial and tem- poral distribution of the atmospheric C02 concentration and ft.