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31.
华北地区沙尘天气垂直气溶胶直接辐射强迫 总被引:1,自引:0,他引:1
利用CALIOP数据和SBDART(Santa Barbara DISORT Atmospheric Radiative Transfer)辐射传输模式研究了2013~2016年华北地区8d沙尘天气气溶胶及其直接辐射强迫垂直分布特征,分析了气溶胶垂直分布和光学特性对直接辐射强迫的影响.结果表明,气溶胶集中分布在地表及以上3km范围,其中纯净沙尘型和污染沙尘型气溶胶位于上层,污染大陆型气溶胶和烟雾位于下层.大气层顶、地表和大气层的日均气溶胶直接辐射强迫分别是-38.41~-88.44,-74.03~-225.86,9.06~137.42W/m2.0~8km高度范围气溶胶直接辐射强迫是负值,且随着高度的增加绝对值逐渐减小.气溶胶垂直分布对大气层顶、地表和大气层的直接辐射强迫影响较小,但对直接辐射强迫垂直分布影响较大,由气溶胶廓线差异造成的同一高度层气溶胶直接辐射强迫最大差值能达到31.18W/m2.气溶胶光学厚度和单次散射反照率对直接辐射强迫影响明显.消光能力相同时,吸收性气溶胶对短波太阳光的衰减作用大于散射性气溶胶,后向散射比例大的气溶胶大于后向散射比例小的气溶胶. 相似文献
33.
针对空气质量状况的预防和治理,提出了基于线性回归的空气质量预测方法。作为时间预测器,更多的是考虑本地的历史数据、过去与未来的状况,挖掘空气质量随时间变化的关系以及变化趋势,为了选取最优的特征,对数据进行分析,找到与空气质量变化关系密切且存在线性关系的特征,以此特征来建立线性回归模型,并使用Cross-Validation方法进行评估验证。实验结果表明线性回归方法能够有效地预测到空气质量的变化趋势,效果良好,具有较强的实用性。 相似文献
34.
响应土壤阴离子类型的盐碱土古细菌群落多样性研究 总被引:2,自引:0,他引:2
为初步解析我国黑龙江苏打盐碱地(HA)、新疆荒漠盐碱地(XD)、山西平原盐碱地(SY)、江苏滨海盐碱地(JD)和天津滨海盐碱地(TB)5个地区的土壤古细菌群落结构多样性,以及其响应土壤不同阴离子类型的分布特征,采用基于Illumin-Hiseq平台的高通量测序技术获得489~604个古细菌可操纵分类单元(OTU).OTU多样性分析结果表明XD的古细菌群落物种丰富度最高,SY和HA分别具有最高和最低的古细菌群落多样性和均匀度;OTU的物种注释结果表明HA以奇古菌门(Thaumarchaeota)为优势菌门,其他土壤均以广古菌(Euryarchaeota)为优势;综合5个样品古细菌群落结构、优势古细菌属和土壤阴离子进行的典范对应分析(CCA)结果显示,XD古细菌群落结构和Haloterrigena属(XD中最优势,相对丰度20.2%)明显的响应土壤SO42-浓度;HA古细菌群落结构和Nitrososphaera属(HA中最优势,62.3%)明显的响应土壤HCO3-/CO32-浓度和pH;JD、SY和TB古细菌群落结构、Halorubrum属(JD和TB中最优势,24.4%和15.6%),和Natronomonas属(SY和JD中第二优势,8.1%和9.2%)明显的响应土壤Cl-浓度.研究结果说明我国不同地域分布的盐碱土受其土壤阴离子类型及其浓度的影响,呈现不同的古细菌群落结构和分布特征.研究结果为我国不同类型盐碱土古细菌资源的挖掘提供依据,也为揭示我国不同类型盐碱土古细菌群落的生态功能提供参考. 相似文献
35.
36.
为了解重庆市九龙坡区城区和城郊大气污染物浓度特征,分析了城区和城郊国控空气站点2014年3月~2015年2月典型污染物的浓度变化。结果表明,除O_3表现出夏高冬低的季节变化趋势外,其它污染物均表现出冬高夏低的季节变化趋势。PM_(2.5)污染最严重,城区和郊区日均值超标率分别为31.4%和33.4%。城区和城郊的PM_(2.5)浓度之间没有显著性差异(p0.05),城郊O_3浓度显著高于城区(p0.01),NO_2、SO_2、CO和PM_(10)则是城区显著高于城郊(p0.01)。 相似文献
37.
38.
Chris J. Matthews David B. Newton Roger D. Braddock Bofu Yu 《Environmental Modeling and Assessment》2007,12(1):27-41
Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The
New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects)
and the extent these parameters interact with each other (second-order effects). This method requires the specification of
two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various
inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and
Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex
processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness
of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition
System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the
sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss
the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring
the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing
these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method
estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown
that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different
metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock. 相似文献
39.
Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization 总被引:6,自引:0,他引:6
Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems. 相似文献
40.
The reduction of SO2 by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH3:SO2 molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO2 emissions was found at 40% excess air, at an NH3:SO2 molar ratio of 5.4. The onset of SO2 reduction occurred at an NH3:SO2 ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO2 reduction.It is difficult to determine how the SO2 reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide. 相似文献