建设项目现状环境影响评价数据引用的探讨

对建设项目环境影响现状监测历史数据的所有权归属进行了分析,环境监测机构具有现状监测成果的所有权,委托方有使用权.应对环境现状监测数据进行知识产权保护,使监测数据得到更好利用.     

Spatial distribution of aerosol pollution based on MODIS data over Beijing, China

With the help of regression analysis,the relationships were detected between aerosol's contribution to apparent reflectance(ACR) derived from Moderate Resolution Imaging Spectroradiometer(MODIS)on board Terra and hourly PM_(10)mass concentration measured at 30 ground-based locations in Beijing for the August of 2003 and 2004.It was shown that there was a good correlation between the ACR and PM_(10)(linear correlation coefficient,R=0.56).On the basis of this relationship,spatial distribution and possible sources of PM_(10)derived from MODIS were analyzed and two frequently heavily-polluted regions were found,namely downtown of the city and the district near Xishan Mountain.These two regions coincidently are also urban heat island centers.The foundings of this paper will be greatly useful for environmental monitoring and urban planning for Beijing,especially for the 2008 Olympic game to be held in Beijing.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.     

Improvement of the antifouling characteristics in a bioreactor of polypropylene microporous membrane by the adsorption of Tween 20

Surface modification by physical adsorption of Tween 20 was accomplished on polypropylene microporous membranes (PPMMs). Attenuated total reflection-Fourier transform infrared spectroscopy (ATR/FT-IR) and scanning electron microscope (SEM) were used to characterize the chemical and morphological changes on the membrane surfaces. Water contact angles and relative pure water fluxes were measured. The data showed that the hydrophilic performance for the modified membranes increased with the increase in the adsorption amount of Tween 20 onto the surface or into the pores of polypropylene microporous membranes. To test the antifouling property of the membranes by the adsorption of Tween 20 in a membrane bioreactor (MBR), filtration for active sludge was performed using synthetic wastewater. With the help of the data of water fluxes and the FE-SEM photos of the modified PPMMs before or after operating in a MBR for about 12 d, the PPMMs with monolayer adsorption of Tween 20 showed higher remained flux and stronger antifouling ability than unmodified membrane and other modification membranes studied.     

基于AHP和DEA模型的农业生态效率评价——以无锡市为例

农业面源污染已成为我国重要环境污染源之一,但由于农业面源污染具有分散、面广、周期长、随机性等特点,在评价上存在较大难度。根据生态效率理论,结合农业生产的特点,建立了综合考虑经济效益和环境影响的农业生态效率评价指标体系,并以江苏省无锡市为例,选取该市1998~2008年农业生产和面源污染相关数据,运用偏好锥的数据包络分析模型（DEA）对其农业生态效率进行了评价分析。结果显示：1998~2008年,无锡市农业生态效率呈现先下降后上升的趋势,近三年累计上升幅度达22%。表明近年来无锡市农业面源污染治理成效显著,农业可持续发展水平显著提高。提出的农业生态效率评价体系和方法为进一步推进农业面源污染治理工作提供了依据     

环境试验数据管理系统的应用

介绍了环境试验数据管理系统的功能及组成,阐述了系统建设的目的和达成的目标,并对其在企业内部的应用效果进行了分析。     

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long‐standing “Digital Divide” in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time‐varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long‐time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed “data rods,” are pre‐generated or generated on‐the‐fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on “data curtains.” The on‐the‐fly generation of data rods uses “data cubes,” NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.     

Supporting Diverse Data Providers in the Open Water Data Initiative: Communicating Water Data Quality and Fitness of Use

Shared, trusted, timely data are essential elements for the cooperation needed to optimize economic, ecologic, and public safety concerns related to water. The Open Water Data Initiative (OWDI) will provide a fully scalable platform that can support a wide variety of data from many diverse providers. Many of these will be larger, well‐established, and trusted agencies with a history of providing well‐documented, standardized, and archive‐ready products. However, some potential partners may be smaller, distributed, and relatively unknown or untested as data providers. The data these partners will provide are valuable and can be used to fill in many data gaps, but can also be variable in quality or supplied in nonstandardized formats. They may also reflect the smaller partners' variable budgets and missions, be intermittent, or of unknown provenance. A challenge for the OWDI will be to convey the quality and the contextual “fitness” of data from providers other than the most trusted brands. This article reviews past and current methods for documenting data quality. Three case studies are provided that describe processes and pathways for effective data‐sharing and publication initiatives. They also illustrate how partners may work together to find a metadata reporting threshold that encourages participation while maintaining high data integrity. And lastly, potential governance is proposed that may assist smaller partners with short‐ and long‐term participation in the OWDI.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.