便携β射线法手工监测PM_(2.5)的可行性研究

提出利用自动射线原理结合重量法的简捷便携特点的便携射线仪手工监测PM2.5的思路,平行比对了便携射线法和手工重量法所测60组PM2.5浓度的监测结果,采用线性回归及T检验、F检验等理论分析了两者数据结果间的有效性和可比性。结果表明,便携式射线仪监测结果与重量法监测结果之间有效可比且得到了两者间的线性回归方程;此外进行了20组数据的实样验证,换算值和真值之间相对误差在8%以内,因而确定了便携射线仪手工监测PM2.5的可行性。     

丹东生态环境监测业务系统设计与实现

丹东生态环境监测业务系统是用于生态环境监测日常业务观测,编制各类观测报文及数据上网传输的实用型业务系统。系统采取多窗157结构框架,合理布局功能窗口界面,兼容了地面气象观测数据文件格式,统一数据检查标准,观测数据处理更为准确有效。并以VB6．0可视化语言为开发工具适应不用版本Windows操作系统。基于生态环境监测数据统计、数据分析和数据发布为一体的多功能业务应用软件。     

振动试验数据管理系统概述

随着近些年振动试验技术的快速发展,对于振动试验数据的保存、管理和统计提出了更高的要求。鉴于此,附属于试验室信息管理系统的振动试验数据管理系统作为振动试验有效的管理工具,必然会成为提升试验室振动试验能力、规范试验技术的有效工具。     

Studying crop sequences with CarrotAge,a HMM-based data mining software

We have developed a knowledge discovery system based on high-order hidden Markov models for analyzing spatio-temporal data bases. This system, named CarrotAge , takes as input an array of discrete data – the rows represent the spatial sites and the columns the time slots – and builds a partition together with its a posteriori probability. CarrotAge has been developed for studying the cropping patterns of a territory. It uses therefore an agricultural drench database, named Ter-Uti , which records every year the land-use category of a set of sites regularly spaced. The results of CarrotAge are interpreted by agronomists and used in research works linking agricultural land use and water management. Moreover, CarrotAge can be used to find out and study crop sequences in large territories, that is a main question for agricultural and environmental research, as discussed in this paper.     

区域空气自动监测数据审核方法与制度的探索

区域空气自动监测网络地理分布范围大、系统仪器设备众多、监测数据以海量计,如何对数据进行审核是一个值得关注的问题.以粤港珠江三角洲区域空气监测网络的实践为例,探讨了区域空气自动监测的数据审核方法与制度.     

Real time remote monitoring of air pollutants and their online transmission to the web using internet protocol

Recent advances in both information and sensor technologies have enabled the development of Real Time Remote Monitoring (RTRM) capabilities for environmental management. An online and real time remote monitoring system for air pollution has been designed and installed at a traffic police station at Punjagutta in Hyderabad, India. The system is optimized using electrochemical sensors and a real time particulate matter analyzer. The system also monitors meteorological parameters such as temperature, humidity, rainfall, barometric pressure, wind speed and wind direction. The system periodically monitors both pollution and meteorological parameters at pre- programmed intervals of hr during peak periods and 1 hr during non peak periods of the day and continuously uploads to a predestinated web site (www.appcb.org/home.htm) using File Transfer Protocol. The web site renders a quick, simple and graphical display of air pollution levels and meteorological parameters and their significance to humans. The present paper highlights design considerations of a pollution monitoring system, system hardware and software requirements and practical limitations and future directions for real time remote monitoring of air pollution.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

物流量统计量纲研究

物流量量纲的统一标准化是物流量研究的基础,影响到物流规划实施的准确性.针对目前物流量统计量纲没有统一标准的问题,提出了物流标准当量这一物流量单位,统一了物流量统计口径,丰富了物流研究的相关于物流量的统计理论,使不同物流实现可加性,并可与市场容量挂钩,为更科学分析、研究和规划物流业打下基础.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Examining Flood Frequency Distributions in the Midwest U.S.1

Villarini, Gabriele, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski, 2011. Examining Flood Frequency Distributions in the Midwest U.S. Journal of the American Water Resources Association (JAWRA) 47(3):447‐463. DOI: 10.1111/j.1752‐1688.2011.00540.x Abstract: Annual maximum peak discharge time series from 196 stream gage stations with a record of at least 75 years from the Midwest United States is examined to study flood peak distributions from a regional point of view. The focus of this study is to evaluate: (1) “mixtures” of flood peak distributions, (2) upper tail and scaling properties of the flood peak distributions, and (3) presence of temporal nonstationarities in the flood peak records. Warm season convective systems are responsible for some of the largest floods in the area, in particular in Nebraska, Kansas, and Iowa. Spring events associated with snowmelt and rain‐on‐snow are common in the northern part of the study domain. Nonparametric tests are used to investigate the presence of abrupt and slowly varying changes. Change‐points rather than monotonic trends are responsible for most violations of the stationarity assumption. The abrupt changes in flood peaks can be associated with anthropogenic changes, such as changes in land use/land cover, agricultural practice, and construction of dams. The trend analyses do not suggest an increase in the flood peak distribution due to anthropogenic climate change. Examination of the upper tail and scaling properties of the flood peak distributions are examined by means of the location, scale, and shape parameters of the Generalized Extreme Value distribution.