生活垃圾强制分类形势下的多源废荧光灯管回收管理机制建议

废荧光灯管的来源广泛,包括工业来源和社会来源,社会来源又包括居民来源,企业事业单位、公共场所等机构来源,具有多来源的特性。废荧光灯管中含有汞,若不经过妥善处理,会造成环境污染,对人的身体健康造成危害。随着国内生活垃圾分类的开展,废荧光灯管作为生活垃圾中有害垃圾的典型类别被强制分类,但仍存在很多问题。本文梳理了我国废荧光灯管的产生情况、LED灯替代情况,并对美国、欧盟、日本和我国国内典型城市的废荧光管理情况进行了总结。针对我国废荧光灯管的回收现状,从责任主体、责任划分、收集渠道、资金机制等角度提出了相关的管理建议,为推动我国废荧光灯管的管理提供借鉴。     

基于RS的成都市城市扩张监测与分析

随着21世纪人口和经济的快速增长,城市扩张速度明显加快,如何快速获取城市的扩张信息并进行分析,对城市的规划和可持续发展具有十分重要的意义。采用监督分类方法对3个时相的成都市建成区进行提取,并分析比较。在此基础上,结合相关的统计数据分析,得出成都市城区的扩张与经济发展密切相关,人口增长与基础设施完善也起到了重要的驱动作用。     

江苏省地理标志概况与价值评估体系构建研究

以江苏省43个地理标志为研究对象,根据国家地理标志的分类方法对其进行分类,构建价值评估体系,探讨地理标志产品的内在价值及发展重点。研究表明,江苏省地理标志类型较为单一,分布均匀;开发程度不同,可分为开发匮乏型、有待开发型和开发成熟型。通过价值体系评价可见,江苏省应重点挖掘产品的自身特色,发展价值意义突出的地理标志。     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

供水管网震后流量监测点的动态分级优化布局研究

为了提高管网地震监测点布局的准确性和合理性,基于管网微观水力计算模型和动态分级法,提出供水管网震后流量监测点的动态分级优化布局模型。首先,利用管网微观水力计算模型计算管段流量的影响系数,构建管段的影响系数矩阵,并利用信息熵确定管段权重;其次,标准化处理影响系数矩阵,通过聚类迭代提出供水管网地震流量监测点优化布局的动态分级方法,对供水管网震后流量监测点进行优化布置分级评定;最后,根据工程实例进行方法实践,结果表明:供水管网中的管线分类较为科学合理,地震监测点在供水管网上分布也比较均匀,而且该模型在一定程度上消除了人为因素的影响,保障了震时管网的监控效果和日常建设的合理性。     

基于随机森林的突发事件分级模型研究

突发事件的分级是快速响应和有效应对的基础,为了解决目前突发事件分级宽泛、主观性强和动态适应性弱等问题,将多分类器集成引入突发事件的分级过程中,借助随机森林组合分类器,针对突发事件特征,构建突发事件分级的随机森林模型,形成突发事件分级过程,进而对事前的应急预案制定、事中的应急资源配置和应急决策提供有力支撑;最后,以2014-2016年洪涝灾害突发事件为例检验构建的模型和过程。研究结果表明:与支持向量机方法相比,通过检验随机森林组合分类器分类结果准确率达到97.56%,在突发事件分级的应用上是可行的,进而可为突发事件的快速响应和应急决策提供信息支撑和参考依据。     

不同天气型下武汉城市圈PM2.5污染及大气层结特征分析

利用2015—2019年PM_2.5和气象要素观测资料、NCEP和ERA5再分析资料,分析不同天气型下武汉城市圈PM_2.5区域污染时空分布、天气尺度环流和大气层结特征.结果表明,城市圈污染以武汉为中心,多为轻度-中度污染,西部重于东部.造成武汉城市圈区域污染增长的天气形势包括4类,分别为冷高压底前部型、高压后部型、均压场型和低压倒槽型.4类污染天气型均有较低的混合层高度和地表通风系数,且边界层存在弱下沉运动和逆温,抑制污染垂直扩散.但气象要素影响PM_2.5污染的机理各异：冷高压底前部型主要为大气压梯度引导偏北大风带来污染物远程输送,边界层冷平流导致低温、锋面逆温和浅薄高湿层(65%～80%),强输入性污染配合吸湿性累积增长造成严重污染,逆温厚度对PM_2.5增幅作用明显;低压倒槽型东南风输入污染弱,但高温、低压引起气流辐合导致本地污染汇积,边界层暖平流带来平流逆温和深厚湿层(1000～750 hPa),逆温层底高偏低、厚度偏厚,促进污染物在近地面吸湿增长;高压后部和均压场型均为浅薄湿层(1000～975...     

基于快速聚类方法分析常州市区PM2.5的统计特性

运用统计方法研究常州市区2013~2014年6个国控点六项基本污染物(SO_2、NO_2、CO、O_3、PM_(2.5)和PM_(10))月平均浓度变化,结果表明,除O_3外,其它五项污染物月平均浓度夏季较低冬季较高.颗粒物与风速之间的关系为PM_(2.5)浓度随风速的升高一直降低,PM_(10)随风速的升高浓度先降低后升高.采用快速聚类分析(k-means)并运用SWV和DIV指数对六项基本污染物进行分类,得到4个样本分类.与依据颗粒物化学成分或粒径谱对PM进行源解析方法不同,本研究更多是从PM_(2.5)与其它污染物相关关系以及污染程度等角度按照欧式距离进行分类.不同类中PM_(2.5)来源明显不同,类1中PM_(2.5)与化石燃料燃烧排放密切相关,类2与O_3密切相关,类3与城市不完全燃烧排放、区域灰霾污染密切相关,类4可以归类于城市"背景"类.快速聚类分析结果也表明常州市区PM_(2.5)有着复杂的来源.     

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.