工业区域网格化环境管理模式研究

工业区域由于环境状况复杂、差异性大而难以进行系统、有效的环境管理.以华东某工业区域为例,对网格化环境管理模式及区域污染指数(RPI)评定指标体系进行了研究,并对2007年该工业区域各网格环境状况进行了评定.结果显示,环境等级为优良、合格、轻污染、中污染、重污染的网格面积分别为34.14、130.32、79.47、45.36、3.10 km2,环境评定结果与现状基本相符.实证表明,在环境状况复杂、差异性大的工业区域,网格化环境管理模式是一种有效的管理方法.同时,在网格化环境管理模式的具体实践中,应注意环境状况评定指标体系的设定、计算机技术的应用、环境数据的实效性、网格交界处环境数据的处理以及管理机制等问题,要结合工业区域特点找出具体方法.     

对当前规划环境影响评价存在问题的探讨

根据战略环境评价的基本内涵.针对当前中国规划环境影响评价实践中存在的诸多问题,重点选择替代方案不完善和评价结果不能有效执行这2个突出问题.并进行了产生原因的深层分析.随后结合规划环境影响评价基础理论及现实需要,提出替代方案优化论证和评价结果有效执行的基本思路,以期对规划环境影响评价制度的进一步完善提供建议.     

论基于EGIS平台的放射源管理系统的开发

放射源管理系统是一种基于环境地理信息系统平台的资源管理系统,是GIS技术与环境监测技术、环境管理技术、数据库技术等各种环境信息分析和处理技术的集成。系统为环保部门提供了一个功能强大的空间信息服务和管理工具,可以直观、方便地获取放射源的监控、管理等数据信息,为环境管理部门的决策提供依据。     

基于预警视角的南京市资源环境承载力评价研究

参考国家相关指南并结合南京市实际,以区级行政区为评价单元对南京市进行资源环境承载力评价。基于预警视角从资源、环境、生态等维度选取典型指标构建评价指标体系,分别进行针对资源、环境与生态的基础评价和针对农产品主产区的专项评价。采取"短板效应",结合基础、专项评价结果进行南京市资源环境承载力集成评价,为南京市资源环境承载力评价预警工作提供基础数据支撑,并从水资源、土地资源、大气环境、水环境、生态系统等方面进行超载因子识别与分析,提出相应的管控对策建议。     

高等级公路环境敏感点的大气影响评价方法探索

1 评价要求高等级公路的大气环境影响分析除了对一般路段进行大气污染现状及预测评价外,对于评价范围内特殊的环境敏感点还必须作特殊分析,这样才能完整地表达整条线路的大气环境影响情况.浙江省环境保护局制定的公路评价规范对此提出了较高的要求,这些要求主要包括三方面内容:一是如果在环境敏感点附近有比较方案,则应通过计算说明哪个方案对环境敏感点的影响较小,从而为选定路线方案提供环保上的意见.二是在环境敏感点应进行现状背景实测,从而为预测叠加提供本底浓度值.三是在环境敏感点的预测评价上考虑附近地理位置及气象条件的变化,结合实际情况选     

环境应急信息管理平台

环境应急信息管理平台是以信息化技术手段作为支撑的、面向环境应急事件的综合性的信息管理、事态预测、应急决策系统。系统以GIS为基础,可以快速地了解突发环境事件的发展状况,同时通过对环境背景数据库、空间信息数据库、环境应急专项数据库中的相关知识与数据进行综合分析,建立污染物扩散模型以及辅助决策模型,为决策者快速提供一个直观、科学、合理、优化的应急处置方案和指挥调度方案,并能够为事件后期评估、科学制定善后处理措施提供必要保障。     

城镇化建设对旅游资源的影响及策略探讨

分析了城镇化建设对旅游资源的影响,提出了城镇化建设对旅游资源的保护措施,并研究了城镇化建设与旅游资源开发利用中需注意的问题.在旅游的产业链条上,把环境资源作为利益相关者的必然组成,从而实现旅游的可持续发展.     

环境污染问题对资源型城市发展的制约与应对策略分析

资源型城市经济快速发展的同时,存在的环境污染问题均较为严重.为维持城市经济的可持续发展,资源型城市实施战略转型势在必然,在这个过程中,环境保护必须纳入转型战略整体规划中.以"钢都"攀枝花为例,分析了资源型城市发展中的环境制约因素,强调在转型战略中应充分考虑环境保护和生态恢复等问题,并提出循环经济、清洁生产等是攀枝花市资源型城市战略转型中可采取的缓解环境危机、实现经济与环境协调发展的有效措施.     

基于GIS城市道路交通噪声环境管理系统的构架与实现

详细介绍了基于GIS技术开发城市道路交通噪声环境管理系统的构架与实现.该系统的开发工作主要包括:噪声数据库设计、噪声数据管理、交通噪声的模拟和交通噪声影响统计.系统采用了数据库技术、GIS技术和交通噪声预测模型,综合考虑实际情况,对城市噪声环境进行管理和模拟.从实例结果分析可见,模拟结果能达到实际使用的要求.该系统能为城市规划、城市环境评价提供信息和技术支持.     

基于区域环境风险敏感性分析的石油化工行业规划环境风险评价

石油化工行业规划涉及多个石油化工项目的选址和多个备选方案的比选,增大了环境风险评价的不确定性.基于区域环境风险敏感性分析,研究了环境风险评价方法.在传统的环境风险分析框架即事故的发生概率(风险度)与事故的环境后果的基础上,考虑区域环境风险敏感性对环境风险评价的影响,对规划布局涉及区域的环境风险进行评价,最后将该方法初步应用于实际案例中.研究表明,该方法可以有效地分析多个备选方案的规划的环境风险,分析结果直观、可行,且可以辅助决策者对产业布局的合理性作出准确的判断,通过对该方法在应用中存在问题的分析,展望了规划环境风险评价的进一步工作.     

Comment on regression analysis of air quality data

A simple numerical experiment demonstrates that the reduced major axis regression, rather than standard linear regression, is likely to be the method of choice for the regression analysis of air quality datasets. The case used for illustration is that of determining equivalence of alternative PM10 measurement systems.     

Urban influence on cloud cover estimated from satellite data

Quantitative assessment of the influence of a big city on the cloud cover was made using time series of satellite measurements. Data from the advanced very high resolution radiometer (AVHRR) on board NOAA satellites received during 1993–1996 over the Central European part of Russia have been processed to derive statistics on spatial distribution of cloudiness for a territory of approximately 7000 km² covering Moscow (55.7 N, 37.6 E) and adjacent areas. Two basic cloud cover characteristics were studied: the total fractional cloud cover and the frequency of occurrence of cloudless scenes (or the clear-sky frequency). Results of the study show that the urban effect is most pronounced during spring and summer periods when a considerable increase in the cloud amount over most of the built-up city area is observed. The winter period presents only a slight evidence of the urban-induced modification of the cloud amount spatial distribution pattern. The average clear-sky frequency in the centre of the city was found to be 5.4% lower than in the nearest suburbs. No well-defined seasonal variations of the urban–rural difference in the clear-sky frequency were detected.     

ACCESS climate data management

Building on achievements and experience gained through the EU project DAMOCLES and international data management during the International Polar Year, ACCESS, data management was implemented using the same platform as used for DAMOCLES. A metadata-driven approach through which all datasets are properly described with discovery and use metadata was chosen in order to simplify data management and data usage. The system provides automated submission and checking of datasets, search and download as well as visualisation and transformation on user demand and metadata export. Long-term management of ACCESS climate datasets is done within the context of the Arctic Data Centre. This ensures visibility of ACCESS datasets in the context of WMO and GEOSS catalogues. Challenges with ACCESS data management have mainly been cultural with the consequence that the system has been underutilised within the duration of the project duration.     

A comparison of chemical mechanisms based on TRAMP-2006 field data

A comparison of a model using five widely known mechanisms (RACM, CB05, LaRC, SAPRC-99, SAPRC-07, and MCMv3.1) has been conducted based on the TexAQS II Radical and Aerosol Measurement Project (TRAMP-2006) field data in 2006. The concentrations of hydroxyl (OH) and hydroperoxy (HO₂) radicals were calculated by a zero-dimensional box model with each mechanism and then compared with the OH and HO₂ measurements. The OH and HO₂ calculated by the model with different mechanisms show similarities and differences with each other and with the measurements. First, measured OH and HO₂ are generally greater than modeled for all mechanisms, with the median modeled-to-measured ratios ranging from about 0.8 (CB05) to about 0.6 (SAPRC-99). These differences indicate that either measurement errors, the effects of unmeasured species or chemistry errors in the model or the mechanisms, with some errors being independent of the mechanism used. Second, the modeled and measured ratios of HO₂/OH agree when NO is about 1 ppbv, but the modeled ratio is too high when NO was less and too low when NO is more, as seen in previous studies. Third, mechanism–mechanism HO_x differences are sensitive to the environmental conditions – in more polluted conditions, the mechanism–mechanism differences are less. This result suggests that, in polluted conditions, the mechanistic details are less important than in cleaner conditions, probably because of the dominance of reactive nitrogen chemistry under polluted conditions.     

Registering and analysing data on detection of chemicals in the environment

As part of the research project “information system for environmental chemicals” a factual databank on a testset of 68 chemicals was developed. The set-up of the databank is described and the analysis of the results is shown for benzo(k)fluoranthene using a graphical boxplot illustration.     

数据挖掘平台在珊瑚礁生态系统保护中的初步构建研究

近年来,由于疾病、污染、海洋温度上升以及人类的过度利用,珊瑚礁正面临着致命的毁灭.为了保护珊瑚礁生态系统,迫切需要收集和分析数据,找出影响珊瑚礁生存的主要因素.数据挖掘技术可用于复杂系统的行为建模和预测,将数据挖掘算法与珊瑚礁生态系统数据相结合,构建生态数据挖掘平台,为预测珊瑚礁的生长趋势提供决策支持.针对海洋数据多源性、多态性和多样性的特点,提出改进的数据挖掘平台,并详细论述了数据源层、ETL工具层和数据仓库的结构和功能.     

Recommendations on the use of satellite remote-sensing data for urban air quality

In the last 5 yr, the capabilities of earth-observing satellites and the technological tools to share and use satellite data have advanced sufficiently to consider using satellite imagery in conjunction with ground-based data for urban-scale air quality monitoring. Satellite data can add synoptic and geospatial information to ground-based air quality data and modeling. An assessment of the integrated use of ground-based and satellite data for air quality monitoring, including several short case studies, was conducted. Findings identified current U.S. satellites with potential for air quality applications, with others available internationally and several more to be launched within the next 5 yr; several of these sensors are described in this paper as illustrations. However, use of these data for air quality applications has been hindered by historical lack of collaboration between air quality and satellite scientists, difficulty accessing and understanding new data, limited resources and agency priorities to develop new techniques, ill-defined needs, and poor understanding of the potential and limitations of the data. Specialization in organizations and funding sources has limited the resources for cross-disciplinary projects. To successfully use these new data sets requires increased collaboration between organizations, streamlined access to data, and resources for project implementation.