能源承载力预测分析方法的研究与应用研究

能源需求和人口、经济密切相关。能源需求分析是在一定的人口和经济增长假设下进行的。从投入产出角度看,能源需求的高低取决于终端需求与满足终端需求的中间过程。经济结构的变化,经济增长模式的选择,技术进步,优质能源的可获得性,环境保护要求等因素会对终端需求和中间过程产生影响。由于资源对国家和地区的重要性,资源承载力的研究显得尤为重要。因此有必要对一个区域的能源需求量作出预测和分析,提高区域发展和管理的科学性,从而实现区域的可持续发展。     

An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly.     

某危险废物填埋场地下水污染预测及控制模拟

以某危险废物填埋场为研究对象,在收集其水文地质资料基础上,运用Visual Modflow建立填埋场地下水水流和溶质运移耦合模型,对填埋场防渗层发生渗漏后,渗滤液中Cr6+在地下水中的运移过程以及地面硬化、防渗墙和排水沟3种污染控制措施对污染羽阻隔效果进行模拟预测.结果表明,Cr6+随地下水流方向运移形成污染羽,10 a后污染羽到达水塘边界,运移距离约为1 450 m,但随后10～20 a之间污染羽扩散范围没有明显扩大;地表硬化后,20 a内污染羽未扩散至水塘边界;防渗墙设置到上层含水层底部时,监测井Cr6+浓度高于未设置防渗墙时浓度,设置到下层含水层底部时,Cr6+浓度与设置于上层含水层时监测结果相反;排水沟日排水量达到2 642 m3时能有效控制污染羽扩散,20 a后污染羽尚未污染监测井;地表硬化与排水沟组合控制污染物扩散,效果最佳,同时排水沟日排水量可减少为1 878 m3.因此,当填埋场发生渗漏时,建议采用设置排水沟与周边地表硬化组合的地下水污染控制措施.     

基于裂区设计的大气能见度拟合及预测模型

通过收集分析广州能见度及影响因子数据的特征,使用R-project统计软件作为建模工具,采用多层裂区实验构建模型基本框架,选择影响显著的因子进行变量变形处理,对年、月、日、小时的数据特征进行层层分割设计,并在对应层次引入代表时间含义的虚拟变量以提高模型的表征水平,加入二次项、交叉项等提高模型的精度,得到拟合度高、适用性强的能见度拟合及预测模型。     

华南沿海某大气背景点黑碳气溶胶污染特征

黑碳气溶胶(BC)因其显著的气候效应和对人类健康的危害而成为研究的热点。研究背景点位BC的浓度水平和来源特征有助于掌握BC在区域尺度上的辐射强迫特性和环境影响。2009年秋季在华南沿海某区域大气背景点进行了为期约40 d的BC在线观测。观测期间BC的平均浓度为(2.34±1.33)μg/m3,与其它区域背景点相比处于较高水平。利用中尺度天气研究和预报系统WRF模拟的高分辨率三维气象场数据驱动HYSPLIT-4反向轨迹模式,模拟观测期间每小时的气团轨迹,将所有轨迹分为来源特征明显的东北沿海、北方内陆、香港方向和东南海面方向四类。当受到东北沿海来源气团影响时,BC的浓度为平均水平的1.4倍,BC和CO有较好的线性相关关系,而其它三类气团影响时的BC浓度都低于平均浓度,且BC和CO的相关关系很差,说明来自东北沿海地区的较近距离区域传输是影响该背景点大气BC的主要源区。     

基于可公度法的航材故障预测

介绍了可公度性的概念和可公度信息预测理论。应用可公度信息预测理论,以故障时间窗口期为研究对象,对航材故障预测进行了初步探索,进而建立了一种较为实用的预测模型,并且给出了具体算例,验证所建模型的科学性和有效性。通过与指数平滑法预测模型对比可看到可公度预测模型精度更高且计算模型更为简单,为航材故障次数预测提供了一种解决方案。进而可以更好地应用在实践当中,提高航材管理水平,保障飞行任务的完成。     

基于指数平滑法的环境噪声污染预测模型及应用

为了研究城市环境噪声污染的数学模型,通过对厦门市环境噪声的实际情况的分析并结合指数平滑预测模型,提出了符合当前环境噪声的分段三次指数平滑模型。计算了不同平滑系数时数学模型的精度,同时应用建立的数学模型对福州市10年内的噪声污染进行了预测。预测发现,噪声污染呈逐年减小的趋势,到2020年区域环境噪声和交通噪声污染分别达55.09 dB(A)和67.19 dB(A)。指数平滑法的应用效果与平滑系数的选取关系密切,应用时要根据预测的精度要求和预测期限的长短,适当选取平滑系数,并对预测的精度进行分析。结果表明基于该方法预测未来中期环境噪声准确率满足使用需求,并为其他环境噪声预测提供一种新的方法。     

基于小波变换与传统时间序列模型的臭氧浓度多步预测

采用最大重叠小波分解与重构方法,将影响O3小时浓度的不同时间尺度的物化过程分离出来,以提高序列的光滑性.同时,选择合适的传统时间序列模型(如ARIMA模型等)来描述不同过程的序列特征,并分别拟合预报.最后,在建模中引入24 h季节项,以实现提前24 h-次性预测未来1d的O3逐时浓度.结果表明,预报的平均相对误差为12.92％,平均绝对误差和均方根误差分别为10.04 μ.g·m-3和13.98μg·m-3,预报值与实测值的相关系数和匹配指数分别为0.96和0.98.随着预测期的延长,预报误差仍处于可接受范围内.该方法同样适用于每日最大O3小时浓度预报,研究结果为发布天气预报式的空气质量预报提供了新思路,便于公众规划出行并减少大气污染暴露.     

China's Present Situation of Coal Consumption and Future Coal Demand Forecast

This article analyzes China's coal consumption changes since 1991 and proportion change of coal consumption to total energy consumption. It is argued that power, iron and steel, construction material, and chemical industries are the four major coal consumption industries, which account for 85% of total coal consumption in 2005. Considering energy consumption composition characteristics of these four industries, major coal demand determinants, potentials of future energy efficiency improvement, and structural changes, etc., this article makes a forecast of 2010s and 2020s domestic coal demand in these four industries. In addition, considering such relevant factors as our country's future economic growth rate and energy saving target, it forecasts future energy demands, using per unit GDP energy consumption method and energy elasticity coefficient method as well. Then it uses other institution's results about future primary energy demand, excluding primary coal demand, for reference, and forecasts coal demands in 2010 and 2020 indirectly. After results comparison between these two methods, it is believed that coal demands in 2010 might be 2620-2850 million tons and in 2020 might be 3090-3490 million tons, in which, coal used in power generation is still the driven force of coal demand growth.