多尺度分割与特征优选下的盐碱地提取

土地盐渍化作为一种土壤灾害,严重制约着社会经济与农业的发展。对盐碱地进行实时监测,可为盐碱地的评价改良提供科学依据。由于盐碱地的信息复杂、提取精度不高,因此本文以高分六号(GF-6)卫星遥感影像为数据源,采用分形网络演化算法(fractal net evolution approach,FNEA)进行影像对象的多尺度分割,从面向对象的角度减少高分影像分类结果中的椒盐噪声问题,通过计算图像对象的局部方差和变化率来确定适宜的盐碱地分割尺度。利用基于特征选择的相关性算法(correlations-based feature selection,CFS)与Relief F算法分别对由光谱、纹理、形状、遥感指数构成的初始特征空间进行特征优选,精简特征子集,解决特征数量冗余问题,以此来优化随机森林对盐碱地提取精度。结果表明:CFS约简后的特征子集更小,精度更高,说明在盐碱地提取过程中,筛选特征数目能够减小冗余数据对提取精度的影响。CFS优化后的随机森林对盐碱地的提取效果较好,该方法总体分类精度达到83.7%。     

数值模拟结合SF_6示踪法确定煤层钻孔瓦斯抽采有效半径

为准确确定煤层钻孔的瓦斯抽采有效半径,实现最优钻孔设计及最佳抽采效果,根据煤层瓦斯流动理论与煤岩体变形理论,建立钻孔抽采煤层瓦斯的气固耦合数学模型。并利用COMSOLMultiphysics软件,模拟SF6气体在瓦斯渗流场内的运移过程。利用SF6气体示踪法进行现场测试。依据相似定律,结合模拟与实测结果确定钻孔抽采有效半径的范围。以黄陵集团一号煤矿306工作面为例进行试验研究。试验结果表明,模拟结果与实测结果基本吻合;在钻孔直径为94 mm,抽采负压为15 kPa的条件下,预抽30天后,试验工作面抽采有效半径为5.88 m。     

利用FLEXPART模式反演中国区域SF6排放量

六氟化硫(SF_6)是一种长寿命卤代温室气体,被列为《京都议定书》限排物种.随着经济高速发展,中国的SF6排放量受到世界各国的关注.采用传统的"自下而上"清单方法估算SF6排放量时,所需排放因子、活动水平数据的准确性和时效性存在较大局限.因此,本文利用拉格朗日粒子扩散模式FLEXPART,结合2009年北京上甸子区域大气本底站SF6浓度观测资料,尝试建立中国区域SF6排放量的反演方法.结果表明,初步反演的2009年中国区域SF6排放量为1.25×103(0.53×103~1.97×103)t·a-1,与文献结果相当,源排放量的不确定性从1.05×103t·a-1减小到0.72×103t·a-1.与先验源相比,反演源的相关系数从0.37提高到0.43,均方根误差减小了2.64%.     

Treatment of 2-phenylamino-3-methyl-6-di-n-butylaminofluoran production effluent by combination of biological treatments and Fenton＇s oxidation

High strength refractory organic stream is produced during the production of 2-phenylamino-3-methyl-6-di-n-butylaminofluoran （One Dye Black 2, abbr. ODB 2）, a novel heat-sensitive material with a promising market. In this study, a combination of acidificationprecipitation, primary biological treatment, Fenton＇s oxidation and another biological treatment was successfully used for the removal of COD from 18000-25000 mg/L to below 200 mg/L from the ODB 2 production wastewater in a pilot experiment. A COD removal of 70%-80% was achieved by acidification-precipitation under a pH of 2.5-3.0. The first step biodegradafion permitted an average COD removal of 70% under an hydraulic residence time （HRT） of 30 h. By batch tests, the optimum conditions of Fenton＇s oxidation were acquired as： Fe^2＋ dose 6.0 mmol/L; H2O2 dose 3000 mg/L; and reaction time 6 h. The second step biological treatment could ensure an effluent COD below 200 mg/L under an HRT of 10 h following the Fenton＇s treatment.     

BiOBr/Bi2MoO6异质结的构筑及对甲基橙的吸附/光催化性能的协同作用机制

采用简单的沉积-沉淀法合成了BiOBr/Bi_2MoO_6(BOB/BMO)异质结,采用XRD、XPS、TEM、SEM、EDS、FT-IR、UV-Vis-DRS、PL、PC和EIS等测试技术对光催化剂的物相组成、形貌、光吸收特性和光电化学性能等进行系统表征,并以模型污染物甲基橙(MO)的吸附和光催化降解作为探针来评价BiOBr/Bi_2MoO_6异质结的吸附性能与光催化活性增强机制.SEM和TEM分析结果表明,所得Bi_2MoO_6微球由大量厚度约为20~50 nm的纳米片组成;沉淀-沉积法所得样品的形貌分析显示,尺寸约为10 nm的BiOBr量子点均匀沉积在Bi_2MoO_6微球表面,形成的新颖的BOB/BMO异质结.N2吸附/脱附结果表明,Bi_2MoO_6和BiOBr形成异质结具有大的比表面积(64.94 m2·g-1),且表面孔结构丰富.吸附/光催化降解实验结果表明,与纯Bi_2MoO_6或者BiOBr相比,BOB/BMO异质结表现出更好的吸附性能和光催化活性.吸附/光催化协同作用机理分析表明,BOB/BMO异质结具有大的比表面积和丰富的孔结构是其吸附性能增强的主要原因.此外,光致发光(PL)谱、光电流(PC)和交流阻抗(EIS)分析进一步揭示了BOB/BMO异质结有利于光生载流子的分离与转移,导致光催化活性增强,二者的协同作用使其对MO具有优越的去除性能.此外,BOB/BMO异质结较稳定,重复使用性能良好,有望用于MO废水的实际处理.     

亚超临界水技术在废旧尼龙6解聚中的应用

研究了尼龙6在亚超临界水中的解聚反应,以期为废旧尼龙6的回收利用提供技术参数.实验分别利用气质联用仪和紫外分光光度计对解聚后的液相产物进行定性和定量分析,并考察了不同的反应温度、反应压力和反应时间对液相产物收率的影响.结果表明,液相产物绝大部分为己内酰胺;解聚的最佳条件为370 ℃、25 MPa、60 min;己内酰胺最大收率为96%.通过动力学分析和Arrhenius关系计算,得出尼龙6亚超临界水解聚的活化能为64.4 kJ/mol.     

气质联用法测固定污染源中三氟甲烷、四氟甲烷、六氟乙烷和六氟化硫

建立了固定污染源排气中三氟甲烷、四氟甲烷、六氟乙烷和六氟化硫的采样和气质联用分析方法,检出限分别为0.06、0.15、0.21、0.71 mg/m3,精密度在3.2%以下,相关系数大于0.999 6,并对浙江省内2家典型企业排放的温室气体进行了监测,实际样品监测结果表明,该方法能够满足废气中4种温室气体的监测要求。     

光度法测定水中己二胺

本文报道了在碱性介质中,沸水浴条件下,己二胺与２,４二硝基氯苯反应生成黄色的１,６二（２,４二硝基苯胺）己烷化合物,用氯仿萃取后于波长４２０ｎｍ处,用２０ｍｍ比色皿比色测定。文中对碱的用量,反应温度及时间,显色剂用量及萃取效率等进行了较详细研究,确定了最佳实验条件并进行了废水样品分析,结果满意。     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.