基于水热因子波动的呼伦贝尔草原产草量模型

基于多年气象资料(温度和降水量)和产草量监测数据,采用相关分析、主成分分析和回归分析等方法,构建呼伦贝尔草原产草量与气象因子统计学模型,并对二者之间的关系进行了分析.结果表明:利用水热波动因子建立的多项式回归模型具有较好的拟合效果,所建立的呼伦贝尔草原产草量预测模型为y=100.209+1.6410x-0.00559x2.F值显著性检验表明,其复相关系数R2=0.4713,F=8.0239(P=0.0033),在α=0.01水平上显著.利用1989─2009年呼伦贝尔草原产草量数据进行模型精度检验,模型预测精度在85%以上.该预测模型具有选用参数易得、易于代入遥感数据中进行栅格计算、精度高于基于植被指数预测模型等特点.     

AnnAGNPS模型在潋水河流域产水、产沙的模拟评价

日益严重的土壤侵蚀造成了土地退化、水体污染等一系列的环境和生态问题,利用基于过程的数学模型已成为流域土壤侵蚀状况定量评价和控制的有效方法.利用美国农业部开发的流域尺度AnnAGNPS模型,设计了基于地形特征的cell离散方案,在多种地理数据采集和参数化的基础上,对江西兴国潋水河流域1991～2005年的径流、产沙过程进行了分布式计算机模拟.在对产水量进行径流滤波分析的基础上,分别对模型模拟的地表径流和产沙量进行了校正和验证.地表径流模拟结果多年平均相对误差为11.8%,确定性系数R2为0.94,产沙量模拟结果的多年平均相对误差为19.71%,确定性系数R2为0.77.表明AnnAGNPS能较好地模拟潋水流域年、月尺度的地表径流和产沙过程.地下径流模拟结果误差较大,其原因和地下径流模拟模块在潋水流域的适用性有待进一步研究检验.对潋水流域土壤侵蚀定量分析表明,潋水流域的年平均侵蚀模数为1 150.29.t(km2.a)-1,属于轻度侵蚀等级,流域内侵蚀较严重的区域集中分布于居民地附近和公路沿线,其水土流失与人类活动有很大关系.     

Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

Vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.     

崇明东滩湿地沉积物重金属污染的磁诊断

对取自崇明东滩的高潮滩、中潮滩和低潮滩的沉积物柱样进行了磁学、粒度、重金属含量等指标的分析、比较与综合研究. 结果表明:在以粉砂为主的崇明东滩,通过污染负荷指数法进行评价,除低潮滩无污染外,中潮滩和高潮滩均有中度的重金属污染. 选取中度重金属污染的高潮滩沉积物柱样进行粒度、重金属含量以及磁性参数的相关性分析显示,χ_fd,χ_ARM/SIRM与重金属含量和粘土(粒径<4 μm)之间有较高的相关性,并以此建立了磁诊断线性回归模型;χ_fd和χ_ARM/SIRM可作为重金属含量的替代指标.      

Removal of phosphate from wastewater using alkaline residue

Alkaline residue(AR) was found to be an efficient adsorbent for phosphate removal from wastewater. The kinetic and equilibrium of phosphate removal were investigated to evaluate the performance of modified alkaline residue. After treatment by NaOH(AR-NaOH), removal performance was significantly improved, while removal performance was almost completely lost after treatment by HCl(AR-HCl). The kinetics of the removal process by all adsorbents was well characterized by the pseudo second-order model. The Langmuir model exhibited the best correlation for AR-HCl, while AR was effectively described by Freundlich model. Both models were well fitted to AR-NaOH. The maximum adsorption capacities calculated from Langmuir equation were in following manner: AR-NaOH AR AR-HCl. Phosphate removal by alkaline residue was pH dependent process. Mechanisms for phosphate removal mainly involved adsorption and precipitation, varied with equilibrium pH of solution. For AR-HCl, the acid equilibrium pH( 6.0) was unfavorable for the formation of Ca-P precipitate, with adsorption as the key mechanism for phosphate removal. In contrast, for AR and ARNaOH, precipitation was the dominant mechanism for phosphate removal, due to the incrase on pH( 8.0) after phosphate removal. The results of both XRD and SEM analysis confirmed CaHPO4·2H2O formation after phosphate removal by AR and AR-NaOH.     

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.     

合肥城郊典型源头溪流不同渠道形态的氮磷滞留特征

为揭示源头溪流中深潭和曲折沟渠两种典型渠道形态的氮磷养分滞留特征,在合肥城郊二十埠河的某一级支流上,以NH4Cl和KH2PO4为添加营养盐,以NaCl为保守型示踪剂,开展现场示踪实验.在此基础上,利用OTIS模型软件、暂态存储参数和养分螺旋原理,解析深潭和曲折沟渠氮磷滞留特征.结果表明:1深潭的As值较曲折沟渠大,但其α值则较弯曲沟渠小1个数量级,而且As和α值随水文条件变化均不显著;2深潭中主渠道流动水体的NH+4-λ较其暂态存储区的NH+4-λs高2~3个数量级,曲折沟渠的NH+4-λ与NH+4-λs数值较为接近;3深潭中NH+4-Vf较SRP-Vf高1~2个数量级,而在曲折沟渠中,不仅NH+4-Vf与SRP-Vf数值较为相近,NH+4-Sw与SRP-Sw也基本相当;4深潭的NH+4-U较SRP-U高出2~3个数量级,曲折沟渠NH+4-U则较SRP-U高出1~2个数量级;5总的来说,在对NH+4和SRP滞留影响方面,深潭和曲折沟渠存在较大的差异性,且在深潭中NH+4的滞留效应显著超过SRP.     

综合指数影响评价模型在地下水防污性能评价中的应用

针对DRASTIC模型在地下水防污性能评价中存在的不足,提出模型的改进方法,在此基础上构建一套基于DRASTIC模型的综合指数影响评价(DRAICQ)模型,并应用于淮河流域中部某市地下水防污性能评价的实例研究中,绘制了研究区地下水防污性能评价分区图。结果表明:DRAICQ模型的计算结果更符合研究区的实际情况,评价效果较好;研究区地下水防污性能评价分区图对该区制定地下水防污措施具有重要的参考指导作用。     

基于MM5模型的大连市气象场模拟分析研究

基于对MM5数值天气模型,从水文气象耦合的角度入手,运用MM5模型在大连区域建立的模拟模型,逐月对大连市气象场进行模拟,并利用大连市5个气象观测站的资料与MM5的模拟结果相比较。     

杭州市灰霾与非灰霾日不同粒径大气颗粒物来源解析

在2011年典型灰霾和非灰霾天气下,采集了杭州市不同粒径的大气颗粒物样品,测定并分析各粒径段颗粒物的质量浓度及其化学成分;同时采集并分析了主要污染源排放的颗粒物样品,通过CMB(化学质量平衡)模型进行源解析. 结果表明:灰霾天气下,二次粒子是杭州市各粒径段颗粒物的首要贡献源,其对≤1.1、>1.1~3.3、>3.3~5.8和>5.8~10μm粒径段的颗粒物贡献率分别为60.4%、62.2%、54.8%和46.5%. 在一次排放源中,机动车尾气是≤1.1和>1.1~3.3μm粒径段颗粒物的重要来源,贡献率分别为13.8%和12.2%;城市扬尘是>3.3~5.8μm粒径段颗粒物的重要来源,贡献率达到16.0%;而建筑施工尘是>5.8~10μm粒径段颗粒物的重要来源,贡献率为14.2%. 非灰霾天气下,随着颗粒物粒径的增加,二次粒子的贡献率显著下降,对≤1.1μm粒径段颗粒物的贡献率为42.7%,而对>5.8~10μm粒径段颗粒物的贡献率仅为15.5%;机动车是各粒径段颗粒物的重要贡献源,贡献率均在20%以上;煤烟尘是≤3.3μm细粒径段颗粒物的重要贡献源类,贡献率为22.0%;城市扬尘是>3.3~5.8μm粒径段颗粒物的重要来源,贡献率为18.3%;建筑施工尘依然是>5.8~10μm粒径段颗粒物的重要来源,贡献率为21.4%.