Environmental Data in Decision Making in EPA Regional Offices

The mid-Atlantic region of the United States has a wide diversity of natural resources. Human pressures on these natural resources are intense. These factors have resulted in the collection of substantial amounts of environmental information about the region by EPA (both Regional and Research Offices), other governmental agencies, industry, and environmental groups. EPA Regional Offices comprehend first hand the importance of environmental data and are extremely supportive of investments in these data. Environmental data are used prominently in a variety of strategic planning and resource management initiatives. In EPA Region 3, the use of scientifically-sound environmental data is, in fact, one of our strategic programmatic goals. Environmental information is captured and assessed continuously by Regional staff, sometimes working in partnership with other Federal and State agencies, to derive relevant resource management conclusions. The restoration goals for the Chesapeake Bay are based on environmental indicators and resulting data. Attainment of the water quality objectives for streams and coastal estuaries are predicted on monitoring data. Our initiative in the Mid-Atlantic Highlands area uses environmental indicators to measure the condition of forests and streams. Landscape-level indicators will provide unique opportunities for the use of data in planning and management activities in support of the principles of community-based activism and sustainable development. Significant value is added to these data during their use by Regional managers. Regional programs, such as the Chesapeake Bay Program and several National Estuary Programs, are founded in environmental data. Environmental information is used by the Regional program managers to ascertain whether programs are accomplishing their intended objectives. Finally, Regional programs provide a crucial means for disseminating this information to broad segments of the public, so that a better informed and educated client base for effective environmental protection will develop.     

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

Experiences of voluntary early participation in Environmental Impact Assessments in Chilean mining

Citizen participation should ideally occur as early as possible in a project, especially throughout the course of the Environmental Impact Assessment (EIA) study. In Chile, participation occurs after the EIA study has been completed and presented to authorities for evaluation. However, voluntary early participation has become an extended practice in large mining projects for financial and conflict-reduction reasons. The purpose of this study was to explore a variety of these early participation processes happening in large mining projects from 2001 to 2010 and analyze how well these practices measured up to standards and objectives defined in the EIA and participation literature. Beyond the legal implications of such practice, we sought to understand the role of this voluntary procedure within the EIA process and citizen engagement in projects. We found a wide range of objectives, approaches and results, primarily driven to facilitate approval and implementation of the ten projects analyzed. The underlying objective of voluntary participation processes analyzed (whether it seeks to inform, to note or to engage), determined the information presented, participants included, area of influence considered, time devoted to the process and influence of the information collected on EIA and project mitigation measures. Few of the principles for best practice in the literature were present in the ten projects examined. Moreover, given the voluntary and unregulated nature of these processes, purposes and outcomes were often mixed-up with the Indigenous Consultation required under ILO provision 169, or Corporate Social Responsibility programs. This finally revealed that contrary to expectations, an unregulated and early voluntary participation is not having a clear impact in the definition of projects mitigation measures, participants are at risk of being unsatisfied with the resulting agreements and moreover, it does not assure projects implementation or the avoidance of socio-environmental conflict.     

用于环境风险评价的大连湾溢油预测模型

基于POM建立了M2分潮的大连湾海域三维潮流场动力模式。利用此动力模式,以"油粒子"模型来模拟溢油在大连湾中的漂移扩散过程。通过欧拉-拉格朗日法,将油膜中心的轨迹和各个时刻的油膜分布情况可视化。溢油预测模型综合考虑了三维流场、湍流、风导输移和波浪破等环境因素对海上溢油行为的影响,考虑了蒸发和乳化过程,预测了溢油的归宿。本模型旨在为大连湾海上溢油风险评价提供信息。     

An Overview of Data Integration Methods for Regional Assessment

The U.S. Environmental Protections Agency's (U.S. EPA) Regional Vulnerability Assessment(ReVA) program has focused much of its research over the last five years on developing and evaluating integration methods for spatial data. An initial strategic priority was to use existing data from monitoring programs, model results, and other spatial data. Because most of these data were not collected with an intention of integrating into a regional assessment of conditions and vulnerabilities, issues exist that may preclude the use of some methods or require some sort of data preparation. Additionally, to support multi-criteria decision-making, methods need to be able to address a series of assessment questions that provide insights into where environmental risks are a priority. This paper provides an overview of twelve spatial integration methods that can be applied towards regional assessment, along with preliminary results as to how sensitive each method is to data issues that will likely be encountered with the use of existing data.     

环境监测数据的数值修约规则探讨

数值修约问题看似简单,实则行之不易。由于目前并没有一种统一的数值修约方式可以处理实际工作中遇到的各种类型的数据,这就导致环境监测报告及科研论文中普遍存在着分析数据数值修约不规范的问题。分析阐明了数值修约的内涵:一是修,是保留几位的问题;二是约,是如何舍入的问题。在此基础上,提出了数值修约的两条原则:准确性和保守性。最后,总结了环境监测常用数据的数值修约规则。     

区域环境污染负荷分析的干预--效应法

介绍了基于生命周期影响评价模型的干预--效应法,以及该法包括的环境效应类型的确定、环境干预因子的识别与归类、按当量因子法汇总、数据标准化和赋权评估5个技术步骤,并以广州市2003年监测数据为基础,对广州市酸化、富营养化和光化学臭氧合成效应作了研究.结果表明,广州市2003年排放的酸化污染负荷量约为379.5×103 t SO2当量,主要污染物是SO2的排放(占57.4%);富营养化污染负荷量为657.7×103 t NO3-当量,其中最大排放源来自人类生活(占38.4%);光化学臭氧合成污染负荷量为46.4×103 t C2H4当量,主要来自于公路交通运输(占69.8%).赋权评估表明广州市区域性的环境效应主要为光化学臭氧合成,其环境负荷为32.358×103人当量,其次为富营养化和酸化效应,环境负荷分别为8.138×103人当量和7.915×103人当量.     

区域规划环评中大气环境监测点位布设研究

探讨了大气环境监测点位的布设方法,在区域规划环境影响评价布设大气监测点位时,应综合考虑开发区的功能区划分、区内产业分布及环境敏感点分布等情况;结合规划区内外现状及规划实施后重点污染源的位置及排放高度,根据区域污染气象条件,采用Gauss模式预测最大浓度落地点,并以此作为区域大气环境监测点的布设依据.对某区域开发规划案例进行了大气环境监测点位布设研究,通过实践,该布设方法不仅可以反映区域大气环境质量现状的空间分布特征,而且可以为区域大气环境预测提供良好的数据支持,为优化区域规划提供依据;同时,对规划后的污染源最大浓度落地点的监测,可以为单个项目的环境预测提供背景值,起到简化入区建设项目环评的作用.     

地表水环境质量评价数据有效性探讨

通过对上海某区一年地表水手工常规监测与自动监测数据比较,对地表水环境质量评价的数据有效性进行分析,提出在丰水期(非威潮影响期)每月需监测8次(隔3日采样),在枯水期(成潮影响期)每月监测1次.定量解决了上海某区地表水环境质量评价数据有效性争议问题.     

大数据技术在环境监测中的应用

简述了环境监测信息化建设应用现状及问题;分析了大数据技术的特点及其在环境监测信息化中的优势。提出,基于"大数据"技术,可以建设环境监测大数据中心,突破传统关系型数据库局限性,运用大数据的核心技术,实现环境质量综合评价技术的新突破,提升环境状况综合预警能力;应用大数据可视化技术,提高科学决策水平,提高人体健康风险评价能力;建立环保舆情分析云平台,提升公众服务能力。     

一种优化的环境测点信息管理模型及其在环境质量数据管理系统中的应用

分析了环境质量数据管理系统中环境测点信息管理存在的问题。针对地理空间、时间、环境管理服务功能类别三类影响因素,提出了一种灵活、高适应性、结构和层次清晰的基础点位信息管理架构———三维矩阵单元式测点信息管理模型,在信息系统开发中有效地实现了通过通用化的环境测点子集机制来把特定的环境质量数据查询需求转化为数据提取的规范化、结构化流程,较好地解决了环境质量数据为环境管理服务的柔性适应性问题。     

环境磁学在城市地表灰尘重金属污染研究中的应用

随着环境问题日渐突出,地表灰尘重金属污染日益成为研究热点。单纯采用化学方法监测重金属污染具有一定局限性,环境磁学方法以其简便、快捷、经济且无害化的特点在城市重金属污染研究中广为应用。通过文献调研,综述环境磁学在城市地表灰尘重金属污染研究中的应用与研究进展,阐明重金属的主要来源,简述环境磁学的诸多参数,分析磁学参数与重金属的关系,并通过对比不同的磁学分析方法,探讨环境磁学方法在城市地表灰尘重金属污染研究中存在的问题及其发展趋势。     

国家级水环境监测数据传输平台构想

设计的新型国家级水环境监测数据传输系统,将集成现有环境监测数据传输软件的思想,提取现有和未来环境监测数据传输业务的共性需求,设计了具有良好扩展性、通用性的系统架构,充分满足环境监测部门数据传输需求,保障水环境监测数据在各个数据中心之间规范有序地传输,实现系统高度集成互联互通、信息资源充分共享、环保业务紧密互动。     

环境综合分析报告中数据统计问题的探讨

数据统计是编制环境质量综合分析报告的基础与支撑,其优劣程度关系到整个报告的质量。目前报告所需数据涉及领域广泛,统计分析过程影响因素复杂。文章就报告编制过程中进行数据处理工作时存在的问题予以初步探讨,并提出可行的建议与对策。     

环境监测数据异常值的判定及处置

准确、可靠的环境监测数据是环境管理的重要现实依据，因此正确鉴别和处理异常数据是环境监测工作中的关键环节。简述了环境监测异常数据的类型和产生的原因，对异常监测数据的处理措施进行了分析。提出，应建立健全环境监测质量管理体系、重视现场采样的信息化管理、正确填写监测原始记录和加强监测数据的审核。     

The Spatial-Scale Effect of an Atmospheric Environmental Impact Assessment in Regional Strategic Environmental Assessment (R-SEA)

When evaluating the atmospheric environment in regional strategic environment assessment (R-SEA), the variation and choice of the spatial scale have a substantial influence on the conclusions of the assessment. In this study, we used numerical simulation to investigate the spatial-scale effect. Two varying spatial extents and two varying spatial details of pollutant emission data (emission inventories in this case) were provided for numerical modeling, and output distributions of atmospheric pollutants at different air pollution levels were compared. The results show that the resolution and spatial range of data collection do indeed influence the atmospheric prediction and assessment results in R-SEA. The spatial-scale effect is more significant under the air pollution condition than under excellent and good air quality conditions. A comparison of varying spatial extents of emission inventory shows that narrowing the prediction area to a local scale is more conducive to identifying the impact of local pollution sources. A comparison of varying spatial details of emission inventory indicates that a higher resolution is favorable for identifying local high concentrations of pollutants and their locations.     

Temperature-Electrical Conductivity Relation of Water for Environmental Monitoring and Geophysical Data Inversion

Electrical conductivity (EC) is widely used for monitoring the mixing of fresh water and saline water, separating stream hydrographs, and geophysical mapping of contaminated groundwater. The measured EC values at various temperatures need to be reported as corresponding to a standard temperature because EC is dependent on temperature. An arbitrary constant is commonly used for temperature compensation assuming that EC-temperature relation is linear (for example 2% increase of EC per 1 degrees C). This paper examines the EC-temperature relation of natural waters having vastly different compositions and salinities. EC-temperature relation was slightly nonlinear in a temperature range 0-30 degrees C, but the linear equation approximated the relation reasonably well. The temperature compensation factor corresponding to 25 degrees C ranged between 0.0175 and 0.0198. When the mean value 0.0187 was used, the error of estimating EC at 25 degrees C from EC at 10 degrees C was less than about 2% for all samples tested. Temperature compensation factors vary substantially depending on the choice of standard temperature. Therefore, a care must be taken when standard temperatures different from 25 degrees C are used.     

层级化环境质量数据网络直报业务系统的设计和应用

分析了目前环境监测部门的数据传输现状,设计了基于VPN互联网络的环境质量数据层级化直报业务系统,介绍了网络直报系统的业务模型、数据审核和存储策略、系统功能设计及其应用等。     

环境污染区划一种新的多元分析方法

本文应用多元统计分析—ＨｏｔｅｌｉｎｇＴ２检验,对来自客观环境的大气污染实测数据进行了分析,并与常规的ｔ检验、聚类分析方法进行比较,认为该法在环境污染评价问题中,具有较高的分辨环境污染时空分异的效力。     

数据融合技术在环境监测网络中的应用与思考

按照环境监测网络的信息处理结构,将网络划分为采集层、网络层和应用层,归纳了数据级融合、特征级融合、决策级融合3层融合级别,介绍了加权平均、卡尔曼滤波、人工神经网络、支持向量机、遗传算法、贝叶斯系统等在环境监测数据分析中的应用,指出当前面临的数据处理技术不成熟、评价体系不完善和数据质量监管能力不足等问题,提出优化网络结构、数据多元应用和强化决策支持等研究建议。