基于STIRPAT模型的中国城镇生活能源消费影响因素研究

为探究人口规模、收入水平、消费倾向、节能政策和技术等因素对中国城镇生活能源消费的影响,基于拓展的STIRPAT模型并运用2000~2013年中国省际面板数据对各影响因素的效应进行评估。结果显示:城镇生活能源强度、城镇居民消费倾向、人均可支配收入、城镇化率、总人口、政策综合力度6个因素的增长率每变化1%,将会引起城镇生活能源消费量增长率0.9322%、0.8537%、(0.559 2+0.169 2 ln DI)%、0.599 8%、0.408 0%、-0.012 0%的变化,表明除节能政策外,其余5因素均正向促进城镇生活能耗增长。其中生活能源强度对城镇生活能耗影响最大,节能政策虽会抑制城镇生活能耗增长,但作用较为微弱。政府需继续加强节能政策综合实施力度,从而实现生活能源消费领域的节能减排。     

Conceptual Framework for the National Flood Interoperability Experiment

The National Flood Interoperability Experiment is a research collaboration among academia, National Oceanic and Atmospheric Administration National Weather Service, and government and commercial partners to advance the application of the National Water Model for flood forecasting. In preparation for a Summer Institute at the National Water Center in June‐July 2015, a demonstration version of a near real‐time, high spatial resolution flood forecasting model was developed for the continental United States. The river and stream network was divided into 2.7 million reaches using the National Hydrography Dataset Plus geospatial dataset and it was demonstrated that the runoff into these stream reaches and the discharge within them could be computed in 10 min at the Texas Advanced Computing Center. This study presents a conceptual framework to connect information from high‐resolution flood forecasting with real‐time observations and flood inundation mapping and planning for local flood emergency response.     

基于LLE-ELM的矿井瓦斯涌出量预测方法研究

基于局部线性嵌入(Locally Linear Embedding,LLE)算法和极限学习机(Extreme Learning Machine,ELM)神经网络建立矿井瓦斯涌出量预测模型,该预测模型运用LLE算法对矿井瓦斯涌出量影响因素样本进行数据挖掘,得到降维后的有效因子,再将这些有效因子作为ELM神经网络的输入层进行训练和预测。利用某矿井的实测数据进行实例分析,结果表明该预测模型预测速度快,精度高,能够用于矿井瓦斯涌出量预测。     

Integration of Optical and Microwave Remote Sensing Data for Agricultural Land Use Classification

An agricultural land use classification of Oltrepo' Pavese region (in Northern Italy) is performed through integration of remote sensing data from optical and radar sensors. The source of optical data was a Landsat-TM image acquired on April 1994, while the source of microwave data was a contemporaneous image of the new radar sensor SIR-C/X-SAR which was flown on-board the Space Shuttle during an experimental mission over the chosen test site. Then, they were combined through calculation of the principal components of the multidimensional data sets and a final classification was carried out and compared with the classifications obtained from optical and radar recordings separately. Results showed remarkable improvement in the classification accuracy of seedbeds and uncultivated fields with radar recordings and of herbaceous crop type with integrated data. Potential ability of a multi-sensor classification and limits of a single-temporal approach are discussed.     

Advantages of Volunteer-Based Biodiversity Monitoring in Europe

Abstract:  Without robust and unbiased systems for monitoring, changes in natural systems will remain enigmatic for policy makers, leaving them without a clear idea of the consequences of any environmental policies they might adopt. Generally, biodiversity-monitoring activities are not integrated or evaluated across any large geographic region. The EuMon project conducted the first large-scale evaluation of monitoring practices in Europe through an on-line questionnaire and is reporting on the results of this survey. In September 2007 the EuMon project had documented 395 monitoring schemes for species, which represents a total annual cost of about €4 million, involving more than 46,000 persons devoting over 148,000 person-days/year to biodiversity-monitoring activities. Here we focused on the analysis of variations of monitoring practices across a set of taxonomic groups (birds, amphibians and reptiles, mammals, butterflies, plants, and other insects) and across 5 European countries (France, Germany, Hungary, Lithuania, and Poland). Our results suggest that the overall sampling effort of a scheme is linked with the proportion of volunteers involved in that scheme. Because precision is a function of the number of monitored sites and the number of sites is maximized by volunteer involvement, our results do not support the common belief that volunteer-based schemes are too noisy to be informative. Just the opposite, we believe volunteer-based schemes provide relatively reliable data, with state-of-the-art survey designs or data-analysis methods, and consequently can yield unbiased results. Quality of data collected by volunteers is more likely determined by survey design, analytical methodology, and communication skills within the schemes rather than by volunteer involvement per se.     

Simulation of transport and composition changes during a blocking episode over the East Atlantic and North Europe

Transport of atmospheric trace gases during a blocking event in the troposphere and lower stratosphere (UTLS) in August 1997 is studied. Considering the frequency of such events it is obvious that they play a significant role for climate and air chemistry and thus the atmospheric environment. The event has been selected because a unique set of composition observations carried out by the CRISTA (Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere) instrument in the UTLS was available for the period of blocking. The regional European Atmospheric Dispersion (EURAD) model system was used for a detailed analysis focusing on ozone and CFC 11 (CFCl₃, Freon) distributions and their temporal and spatial variability. The combination of the CRISTA data and a regional transport chemistry model enabled a unique analysis of transport behaviour of a blocking. This developed an Ω-structure with a deep cut-off low at the western flank of the blocking high and a trough with highly perturbed trace gas fields on the eastern side. Tropopause heights varied intensively and were bended down to rather low levels in the cut-off low and folds appearing in the eastern trough. Results of artificial tracer experiments are presented which show that polluted air from lower tropospheric levels and – in this case – lower latitudes as well as the North American continent may be lifted up to the UTLS in the anticyclonic part of the Ω-block and transported from there over large distances in streamers. Quasi-periodic variations of CFC 11 flux divergence indicate dynamical coupling of the different domains of the block.     

中国陆地生态信息空间化技术研究(Ⅰ)——气象/气候信息的空间化技术途径

论文提出了构建中国陆地生态系统空间化信息系统的基本设想,并且在回顾国内外气象/气候信息空间化研究的现状基础上,评价了已有的气象/气候信息要素空间化技术的发展,探讨了中国陆地生态系统气象/气候信息空间化的技术途径,概要地介绍了研究小组在近年来的工作中所取得的阶段性研究成果,展望了这些成果的应用前景。我国陆地生态信息空间化技术研究和数据产品的开发是生态学、资源科学和环境科学发展的迫切需求。但建立一个适应于不同科学研究的精度、时空分辨率要求的陆地生态信息空间数据库需要较长期的努力和多学科领域的合作,也需要大量的作为科学研究基础数据平台建设的国家投资。     

基于人口分布与土地利用关系的人口数据空间化研究——以西藏自治区为例

土地是人与自然相互作用的产物,人口分布与土地利用具有非常密切的关系。根据1999年全国市县统计人口数据与各市县土地利用类型指数的相关性分析,发现各市县平均人口密度与各市县各类土地利用指数的复相关系数为0.82,在西藏、青海和海南3省区,复相关系数均达到0.99。以西藏自治区为例,根据市县人口密度与土地利用指数及数字高程的相关关系建立了人口数据空间化模型,并计算出西藏自治区1km×1km分辨率的栅格人口数据。在被选作验证区的3县37个乡镇中,用模型计算出的各乡镇人口密度与各乡镇的实际人口密度的相关系数为0.88。因此,土地利用信息是进行市县级人口统计数据空间化的重要参数,利用土地利用与人口分布之间客观存在的关系可以进行市县级人口统计数据的空间化。     

环境空间决策支持集成系统的设计原理与应用

空间决策支持系统(SDSS)是地理信息系统(GIS)和决策支持系统(DSS)的有机结合.笔者在已有研究成果基础上,以厦门市环境管理空间决策支持集成系统(XME-SDSS)为例,介绍了空间信息集成系统的设计原理和实现方法,包括数据分析模型、系统的数据流、数据库结构以及系统的集成方式.      

Impact of the 1998 Central American fires on PM2.5 mass and composition in the southeastern United States

The impact of the Central American fires on PM_2.5 mass concentration and composition in the Tennessee Valley region during portions of May, 1998, has been quantified. Elevated concentrations of smoke aerosol tracers—fine potassium, (and to a lesser extent, calcium and silicon) and, where available, organic and elemental carbon—were observed in the region during times in which satellite imagery (TOMS and GOES-8) showed regional transport of hazy, smoky airmasses from southern Mexico and adjacent areas of Central America. Back-trajectories from network sites in the Tennessee Valley network were consistent with this regional transport. The extent of transport of extra-regional fine particle mass during May, 1998, is discussed relative to the new US fine particle mass-based standards for fine particulate matter.