地表水水质模型概述

近些年来,我国水环境问题日益凸显,借助水质模型对水污染问题进行研究,并为相关管理和规划提供技术支持已经成为水环境研究的热点。本文阐述了地表水水质模型的概念、发展以及分类,介绍了几种当前比较成熟的地表水水质模型,并对地表水水质模型的未来发展做了展望。     

亚运时段广州大气污染物来源数值模拟研究

利用嵌套网格空气质量预报模式系统(Nested Air Quality Prediction Model System,NAQPMS)研究2006年亚运时段广州的空气质量状况,同时结合污染源追踪方法,分析珠三角各城市的源排放对广州全市、广州二环以内市区、广州6个亚运加强观测站的污染物浓度贡献.结果表明,NAQPMS模式能较好地反映广州各污染物(NO2、SO2、PM10)浓度的变化;广州全市、广州市区、6个亚运加强观测站的污染物最主要来源于本地排放,而周边城市以东莞的贡献最大.3个源受体中,广州市区受本地排放的影响最显著,来自本地的NO2、SO2、PM10的月均贡献率分别为89.5%、75.4%、86.7%;东莞则对6个亚运加强观测站的影响最为突出,其NO2、SO2、PM10的月均贡献率达9.3%、23.8%、21.7%,而日最大贡献率高达19.3%、40.2%、48.7%.因此在大力削减广州本地污染排放的同时,对周边城市特别是东莞实施区域联防联控,将能有效改善亚运场馆附近的空气质量.     

生态足迹模型修正的初步探讨

针对生态足迹应用于区域可持续发展评价的不足之处,采取理论拓展、与其他指标结合、引入基于时间尺度的定量指标等方法,对生态足迹模型的修正进行了初步探讨,为生态足迹模型更好地应用于区域可持续性评价提供了科学指导,为进一步的实例研究提供了理论依据。     

基于SVR的长江经济带水环境承载力评价

基于DPSIRM模型构建区域水环境承载力评价指标体系,并基于SVR模型构建了区域水环境承载力评价模型,利用交叉验证法对SVR模型参数进行优化选择,进一步提高模型预测精度.运用该模型研究了长江经济带2009~2018年的水环境承载力演变趋势及空间差异,结果表明：长江经济带水环境承载力等级整体呈现升高趋势,其中上游城市群承载等级由II级（超载）提升到了IV级（弱可承载）;中游城市群承载等级由II级（超载）提升到了IV级（弱可承载）;下游长三角区域承载等级由I级（重超载）提升到了IV级（弱可承载）.将评价结果与熵权-TOPSIS法的评价结果相比较,相同率达到91.7%,说明SVR模型评价区域水环境承载力可行,评价结果可靠.以下游区域为例,分别对其6个子系统的承载力进行剖析,并运用单因素轮换OAT法对各子系统内的评价指标进行敏感性分析,便于决策者识别指标敏感性.     

大气污染物排放调查监测研究进展

系统总结了当前大气污染物排放调查监测的主要方法及其在全球、区域、局地等不同尺度的典型应用,分析了地面监测、模型模拟与遥感反演3种方法受排放源多样、成分复杂、时空变异显著等因素影响,在尺度效应、成分解析等方面存在的问题。从优化监测方法、改进监测模式、融合监测技术等角度,提出了构建现代化大气污染物排放调查监测网络、开展污染物在不同排放阶段的变化解析研究及在不同圈层间的迁移全过程研究等建议。     

液-弹隔振器设计与试验分析

目的开展液-弹隔振器的设计及试验验证。方法基于反共振原理建立的液-弹隔振器动力学分析模型,推导了其动力学方程。结果建立了液弹隔振器隔振频率与相关参数的关系,依据相关参数完成了液-弹隔振器的设计,并进行了液-弹隔振器动力学性能相关试验,利用动刚度测试法和传递率测试法验证了液-弹隔振器性能,试验验证了液-弹隔振器高静态刚度和隔振频率点下的低动态刚度特点。结论实现了液-弹隔振器的设计,同时液弹隔振器在隔振频率点下达到60%的减振效果。     

A new approach to quantify the degradation kinetics of linuron with UV, ozonation and UV/O3 processes

The degradation of linuron, one of phenylurea herbicides, was investigated for its reaction kinetics by different treatment processes including ultraviolet irradiation (UV), ozonation (O₃), and UV/O₃. The decay rate of linuron by UV/O₃ process was found to be around 3.5 times and 2.5 times faster than sole-UV and ozone-alone, respectively. Experimental results also indicate overall rate constants increased exponentially with pH above 9.0 while the increase of rate constants with pH below 9 is insignificant in O₃ system. All dominant parameters involved in the three processes were determined in the assistant of proposed linear models in this study. The approach was found useful in predicting the process performances through the quantification of quantum yield (rate constant for the formation of free radical HOO⁻ from ozone decomposition at high pH), rate constant of linuron with ozone (k_O3,LNR), rate constant of linuron with hydroxyl radical (k_OH,LNR), and α (the ratio of the production rate of OH and the decay rate of ozone in UV/O₃ system).     

Finding threatened forest areas in the central volcanic mountain range conservation area in Costa Rica

The degree at which tropical forests are exposed to human pressure is spatially dependent. Population density, proximity to roads, terrain slope, logging activities and land distribution projects are well known factors inducing deforestation and forest degradation in Latin America. Using expert knowledge to weight these threat factors and a Geographical Information System for spatial modeling, a multi-criteria analysis procedure is presented, that allows stratifying a study region in categories of deforestation threat. The procedure was implemented in the Central Volcanic Mountain Range Conservation Area (CVMRCA) in Costa Rica with the purpose of finding areas with a combination of physical and socioeconomic characteristics that is particularly predisposing to a high probability of deforestation. To validate the map, the CVMRCA was stratified in categories of deforestation risk, and the result was superposed to historical deforestation data of the period 1986–1996. The good correlation between risk category and historical deforestation (r = 0.91, p < 0.001) indicates that the map can be used as a decision support tool for defining priority areas for conservation action.     

Modelling the fate of hydrophobic organic contaminants in a boreal forest catchment: A cross disciplinary approach to assessing diffuse pollution to surface waters

The fate of hydrophobic organic compounds (HOCs) in soils and waters in a northern boreal catchment was explored through the development of a chemical fate model in a well-characterised catchment system dominated by two land types: forest and mire. Input was based solely on atmospheric deposition, dominated by accumulation in the winter snowpack. Release from soils was governed by the HOC concentration in soil, the soil organic carbon fraction and soil-water DOC content. The modelled export of selected HOCs in surface waters ranged between 11 and 250 ng day⁻¹ during the snow covered period, compared to 200 and 9600 ng/d during snow-melt; highlighting the importance of the snow pack as a source of these chemicals. The predicted levels of HOCs in surface water were in reasonable agreement to a limited set of measured values, although the model tended to over predict concentrations of HOCs for the forested sub-catchment, by over an order of magnitude in the case of hexachlorobenzene and PCB 180. This possibly reflects both the heterogeneity of the forest soils and the complicated and changing hydrology experienced between the different seasons.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.