南京东郊风景区旅游环境容量初步研究

通过对南京东郊风景区的实地考察和问卷调查的统计分析，从旅游者的旅游动机、旅游行为方式等方面论述了旅游环境容量的确定和意义，并提出了调控对策和管理意见。     

Pathways of adaptation of common dandelion cenopopulations to long-term chemical and radiation influences

A comparative study of the seed progeny of dandelions was performed with samples from cenopopulations growing for a long time under conditions of radioactive contamination (the zone of the Eastern Ural Radioactive Trace, EURT) or chemical pollution (the impact zone of the Nizhnii Tagil Metallurgical Plant, NTMP). The viability of seeds proved to decrease in a similar way along with an increase in technogenic pressure, irrespective of its nature. Experiments on acute exposure to heavy metals and γ-irradiation made it possible to reveal the adaptive capacities of the seed progeny from each cenopopulation. The background sample (formed beyond the zone of any impact) was relatively resistant to irradiation and very sensitive to heavy metals. The cenopopulations from the EURT and NTMP zones manifested nonspecific responses to the effects of both habitual and new factors.     

中国经济增长与能源消耗的脱钩——东部地区的时空分异研究

工业时代的经济增长是以大量消耗能源为代价的,直接导致环境污染和资源枯竭。将经济增速与环境压力脱钩的同时,实现将人类福祉与资源消耗的脱钩,是实现绿色可持续发展的焦点问题。采用Tapio基本模型构建中国能源消耗与经济增长的脱钩模型,将1979-2014年的脱钩指数划分为8种脱钩类型。结果说明,绝对而稳态的脱钩是不存在的。虽然大部分年份的中国处于弱脱钩状态,但长时间尺度上,经济增长与能源消耗存在"连接-脱钩-复钩-再脱钩"的动态反复过程。以中国东部地区10省份为例,研究脱钩指数变化的趋势和时间分异情况。结果显示,进入21世纪后该地区复钩的可能性不断增加,特别在经济增速趋缓的背景下,需要警惕以能源消耗驱动经济发展的模式重现。计算并比较脱钩指数的5年均值,研究中国东部地区脱钩的空间分异情况。结果表明,经济增长与能源消耗是否脱钩与宏观政策的调整密切相关。不断提高利用效率以减少能源消耗总量,保持弱脱钩是中国经济发展与能源消耗关系的常态。     

国内外近地表处置场处置技术研究

近年来低、中水平放射性废物由于其数量大,种类多等特点得到了国际上越来越多的关注。近地表处置是这类放射性废物的主要处置技术。本文介绍了国外几个国家的近地表处置场运行情况以及管理经验。陈述了我国西北和北龙两个处置场设计及运行情况,对国内外低中放处置场的处置技术进行比较,借鉴国外近地表处置场的先进经验,提出我国近地表处置场建设的相关建议,为我国新建近地表处置场建设提供参考。     

Basic hydrologic studies for assessing impacts of flow diversions on riparian vegetation: Examples from streams of the eastern Sierra Nevada,California, USA

As the number of proposals to divert streamflow for power production has increased in recent years, interest has grown in predicting the impacts of flow reductions on riparian vegetation. Because the extent and density of riparian vegetation depend largely on local geomorphic and hydrologic setting, site-specific geomorphic and hydrologic information is needed. This article describes methods for collecting relevant hydrologic data, and reports the results of such studies on seven stream reaches proposed for hydroelectric development in the eastern Sierra Nevada, California, USA. The methods described are: (a) preparing geomorphic maps from aerial photographs, (b) using well level records to evaluate the influence of streamflow on the riparian water table, (c) taking synoptic flow measurements to identify gaining and losing reaches, and (d) analyzing flow records from an upstream-downstream pair of gages to document seasonal variations in downstream flow losses. In the eastern Sierra Nevada, the geomorphic influences on hydrology and riparian vegetation were pronounced. For example, in a large, U-shaped glacial valley, the width of the riparian strip was highly variable along the study reach and was related to geomorphic controls, whereas the study reaches on alluvial fan deposits had relatively uniform geomorphology and riparian strip width. Flow losses of 20% were typical over reaches on alluvial fans. In a mountain valley, however, one stream gained up to 275% from geomorphically controlled groundwater contributions.     

Forest Dynamics in the Eastern Ghats of Tamil Nadu,India

The primary deciduous forests in the Eastern Ghats (EG) of Tamil Nadu (TN) India have undergone many changes owing to various need-based forest managements, such as timber extraction for industry, railway sleepers, charcoal, and forest clearance for hydroelectric projects and agriculture, during preindependence and postindependence periods (i.e., from 1800 to 1980). The enactment of a forest conservation act during the 1980s changed the perception of forest managers from utilization to conservation. This study was taken up to assess the forests dynamics in the EG of TN spatially between 1990 and 2003 and nonspatially between 1900 and the 1980s. Landsat Thematic Mapper (TM) and Indian Remote Sensing satellite (IRS) 1D Linear Imaging and Self Scanning (LISS III) data were used to assess forests during 1990 and 2003, respectively. Field floristic survey and secondary data (such as published literature, floras, books, and forest working plans) were used to assess the forest dynamics in terms of forest type and species composition among the preindependence period, the postindependence period, and the present (i.e., before and after 1980). The satellite data analysis revealed a considerable amount of changes in all forest types during the 13 years. The comparison of species composition and forest types between the past and present revealed that need-based forest management along with anthropogenic activity have altered the primary deciduous forest in to secondary and postextraction secondary forests such as southern thorn and southern thorn scrub forests in the middle [400–900 m above mean sea level (MSL)] and lower slopes (<400 m MSL). However, the evergreen forests present at the upper slope (>900 m MSL) and plateau seemed not to be much affected by the forest management. The changes estimated by the satellite data processing in the major forest types such as evergreen, deciduous, southern thorn, and southern thorn scrub are really alarming because these changes have occurred after the implementation of a forest conservation act. The dependence of local people on forests for various purposes in this region is also considerably high, which might be a key factor for the changes in the forests. The results of this study not only provide an outlook on the present status of the forests and the change trends but also provide the basis for further studies on forests in the EG of TN.     

基于透明度的东中国海水质状况遥感评价

水体水质状况对海洋生态环境保护和可持续发展具有重要意义。本文针对东中国海海域,从水体透明度（Z_sd）视角,基于长时序MODIS光学卫星遥感资料,构建了一种评价水体状况的新方法。该方法利用透明度及其变化趋势将水质状况进行分类,将水体分为高值且上升趋势（high and increasing, HI）、高值且无趋势（high and no change trend, HN）、高值且下降趋势（high and decreasing, HD）、低值且上升趋势（low and increasing, LI）、低值且无趋势（low and no change trend, LN）、低值且下降趋势（low and decreasing, LD）6种类型,以此对东中国海的水质状况及其影响因素进行分析。结果显示：近20年来东中国海近岸水体大部分区域呈现LN类型,但江苏近岸（连云港附近）水体呈现LD类型;外海海域大部分水体呈现HN类型,但南黄海南部和东海陆架区的部分区域水体呈现HD类型。外海和近岸海域的水体状况分别主要由悬浮颗粒物中的浮游植物和悬浮泥沙主导,但在浙江—福建近岸,其水体状况可能由两者共同主导。     

基于深度学习的华东地区PM2.5浓度遥感反演

PM_2.5作为大气污染的主要来源,对人类身体健康有着极大的影响.本文提出基于深度学习模型的多要素联合PM_2.5反演方法,以PM_2.5浓度作为真值数据,引入Himawari气溶胶光学厚度(AOD)日数据产品与温度、相对湿度和气压等10个要素作为反演要素.为验证方法的有效性,采用华东地区2016～2018年的数据分季节开展实验,并与传统反演方法进行对比.结果表明,PM_2.5浓度与AOD、降水、风速、高植被覆盖指数呈正相关关系,与矮植被覆盖指数呈负相关关系,与温度、湿度、气压以及DEM的相关性随季节的变化而改变;基于深层神经网络(DNN)反演的PM_2.5精度高于传统的线性和非线性模型,各个季节R²均在0.5以上并且误差较小,其中秋季的反演效果最好R²为0.86,夏季为0.75,冬季为0.613,春季为0.566;模型的可视化结果显示,DNN模型的反演结果更接近地面监测站点插值的PM_2.5浓度分布,分辨率更高且更精确.