喀斯特石漠化的研究现状与存在的问题

喀斯特石漠化是土地荒漠化的主要类型之一。喀斯特生态系统的脆弱性决定了喀斯特生态系统的易损性和退化喀斯特生态系统的难恢复性,但它与发生石漠化并没必然的联系,喀斯特石漠化是岩溶生态系统退化的结果,而不是喀斯特生态系统脆弱性的必然表现。故所指的喀斯特石漠化,特指人为加速的石漠化,属于人为荒漠化的一种类型,但强调喀斯特石漠化的人为成因性,并不是否定自然背景对喀斯特生态系统的制约作用。石漠化土地的分类既要能反映出石漠化发生的严重程度,也要能体现石漠化土地的成因和岩性地貌等地质背景对生态学过程的影响,因此,作者提出以“土地利用类型+植被+岩性+地貌+石漠化程度”对人为加速石漠化过程中石漠化土地进行类型划分,以正确评价石漠化土地的生态环境价值。     

贵阳市乌当区耕地土壤重金属污染现状及其评价

在对乌当区10乡镇耕地土壤进行全面调查的基础上，对土壤重金属污染现状进行了监测与初步评价，结果表明：该区域10乡镇耕地土壤5种重金属元素(Cd、Pb、Cr、Hg、As)的含量变幅较大；全区耕地土壤重金属污染综合评价处于警戒水平，多因子综合污染指数为0．78．其中，金华、朱昌两镇的耕地土壤已受到了重金属轻度污染，多因子综合污染指数分别为1．13、1．22，羊昌、新堡、下坝、东风、水田等5乡镇的耕地土壤处于警戒状态，新场、百宜、偏坡等3乡镇的土壤处于安全状态；Cd、Cr是该区耕地土壤的主要污染元素。     

基于决策树的城市黑臭水体遥感分级

水体黑臭程度遥感监测是了解城市水质现状和综合评价城市水环境治理效果的重要手段.以南京、常州、无锡和扬州为研究区,共采集171个样点,同步测量水质参数和光学参数,分析黑臭水体与一般水体的水色和光学特征,构建决策树模型进行重度黑臭水体、轻度黑臭水体和非黑臭水体（记为一般水体）识别.结果表明：①根据色度可将水体分为1~6类水体,其中,类型1~4为黑臭水体,分别为灰黑色、深灰色、灰色和浅灰色水体,类型5和类型6水体为一般水体,分别为绿色系和黄色系水体;②类型1水体的非色素颗粒物和有色可溶性有机物含量高,但色素颗粒物的吸收并不占主导,类型2和5水体的吸收以色素颗粒物吸收占主导,类型3、4和6水体的吸收以非色素颗粒物吸收占主导;③根据六类水体的反射光谱差异用黑臭水体差值指数（difference of black-odorous water index,DBWI）、三波段面积水体指数（green-red-nir area water index,G-R-NIR AWI）、绿光波段反射率和归一化黑臭水体指数（normalized difference black-odorous water index,NDBWI）构建的水体分类识别决策树,能够有效识别出重、轻度黑臭水体和一般水体;④将决策树模型应用于2019年4月9日扬州的PlanetScope影像上,并利用10个同步过境点进行验证,整体识别精度达到80.00%,K值达到0.67.通过水色分类后的城市水体分级模型方法,可推广应用于类似的水体,为黑臭水体监管提供技术方法.     

Quantifying the characteristics of particulate matters captured by urban plants using an automatic approach

It is widely accepted that urban plant leaves can capture airborne particles. Previous studies on the particle capture capacity of plant leaves have mostly focused on particle mass and/or size distribution. Fewer studies, however, have examined the particle density, and the size and shape characteristics of particles, which may have important implications for evaluating the particle capture efficiency of plants, and identifying the particle sources. In addition, the role of different vegetation types is as yet unclear. Here, we chose three species of different vegetation types, and firstly applied an object-based classification approach to automatically identify the particles from scanning electron microscope(SEM)micrographs. We then quantified the particle capture efficiency, and the major sources of particles were identified. We found(1) Rosa xanthina Lindl(shrub species) had greater retention efficiency than Broussonetia papyrifera(broadleaf species) and Pinus bungeana Zucc.(coniferous species), in terms of particle number and particle area cover.(2) 97.9% of the identified particles had diameter ≤10 μm, and 67.1% of them had diameter ≤2.5 μm. 89.8% of the particles had smooth boundaries, with 23.4% of them being nearly spherical.(3) 32.4%–74.1% of the particles were generated from bare soil and construction activities, and 15.5%–23.0% were mainly from vehicle exhaust and cooking fumes.     

海域有机污染物优先排序和风险分类模糊评判系统

本文提出了对区域性有机污染物优先排序和风险分类和定量评判系统：模糊评判系统。该评判系统以反映污染物的毒性，暴露水平和环境化学性质的７项碜数为指标，通过指标参数的标准化及模糊运算，获得有机污染优先排序和风险分类的定量结果。     

Soil erosion and non-point source pollution impacts assessment with the aid of multi-temporal remote sensing images

Soil erosion associated with non-point source pollution is viewed as a process of land degradation in many terrestrial environments. Careful monitoring and assessment of land use variations with different temporal and spatial scales would reveal a fluctuating interface, punctuated by changes in rainfall and runoff, movement of people, perturbation from environmental disasters, and shifts in agricultural activities and cropping patterns. The use of multi-temporal remote sensing images in support of environmental modeling analysis in a geographic information system (GIS) environment leading to identification of a variety of long-term interactions between land, resources, and the built environment has been a highly promising approach in recent years. This paper started with a series of supervised land use classifications, using SPOT satellite imagery as a means, in the Kao-Ping River Basin, South Taiwan. Then, it was designed to differentiate the variations of eight land use patterns in the past decade, including orchard, farmland, sugarcane field, forest, grassland, barren, community, and water body. Final accuracy was confirmed based on interpretation of available aerial photographs and global positioning system (GPS) measurements. Finally, a numerical simulation model (General Watershed Loading Function, GWLF) was used to relate soil erosion to non-point source pollution impacts in the coupled land and river water systems. Research findings indicate that while the decadal increase in orchards poses a significant threat to water quality, the continual decrease in forested land exhibits a potential impact on water quality management. Non-point source pollution, contributing to part of the downstream water quality deterioration of the Kao-Ping River system in the last decade, has resulted in an irreversible impact on land integrity from a long-term perspective.     

水上溢油环境风险源确定研究

依据泄漏进水域的最大油品量、水域环境敏感性等两个主要因素,研究确定了江苏油田水上(临水)设施环境风险源等级,并针对不同的风险源阐述了降低风险等级的技术方法和预防措施,为加强江苏油田环境风险防患、提高应急处理能力提供了依据。     

北京垃圾分类工作现存问题与对策建议

《北京市生活垃圾管理条例》实施以来,北京垃圾分类工作取得"六升两降"八项成效.基于现阶段北京垃圾分类工作推进情况与存在的痛点、难点问题,提出通过购买第三方服务、借助科技手段与工具、多种渠道多种方式相结合、建立长效监督评价机制等方式,为顺利推进北京垃圾分类工作提供参考.     

基于颗粒物浓度的沙尘天气分级标准研究

沙尘天气在近年对我国城市空气质量造成明显影响。目前我国沙尘天气分级仍然按照气象标准 ,主要是以水平能见度进行分级。文章参考国外的有关标准 ,通过统计近年来我国沙尘天气过程中的颗粒物浓度 ,结合我国沙尘天气的发生情况和特点 ,提出了基于沙尘浓度的沙尘天气分级标准     

An Automated Technique for Delineating and Characterizing Valley-Bottom Settings

Accurate delineation and characterization of valley-bottom settings is crucial to the assessment of the biological and geomorphological components of riverine systems; yet, to date, most valley-bottom mapping endeavors have been done manually. To improve this situation, we developed automated techniques in a Geographic Information System (GIS) for delineating and characterizing valley-bottom settings in river basins ranging in size from approximately 1,000–10,000 km². All procedures were developed with ARC/INFO GIS software and fully automated in Arc Macro Language (AML). The GRID module is required for valley-bottom delineation and slope calculations; whereas characterization (i.e., measuring the width of the valley-bottom zone) requires Coordinate Geometry (COGO) in the ARCEDIT module. The process requires three inputs: a polygon coverage of the analysis area; an arc coverage of its hydrography, and a grid representing its digital elevation. The AML is designed to operate within a wide range of computer memory/disk space options, and it allows users to customize several procedures to match the scale and complexity of a given analysis area with available computer hardware.