Polybrominated diphenyl ethers in house dust in Singapore

The use of polybrominated diphenyl ethers (PBDEs) as flame retardants in Singapore is not strictly regulated; therefore these compounds can be readily found in furniture, electronic devices, and building materials. This study was the first of its kind to be conducted in Singapore to measure concentrations of PBDEs in house dust. Samples were collected from 31 homes in various locations across the island-state of Singapore, and a total eight PBDEs congeners were measured. PBDEs were detected in all 31 dust samples and the number of BDE congener detected per home ranged between 3 and 8. The most abundant BDE congeners found were BDE 47, 99 and 209, with a median value of 20 ng g(-1) dust, 24 ng g(-1) dust and 1000 ng g(-1) dust, respectively. BDE 209 contributed 88% to the median of all the congeners, and BDE 47 and 99 contributed 1.8% and 3.5%, respectively. Different congener profiles were observed between this and studies conducted elsewhere, which is consistent with the use of different commercial PBDE around the world. No significant correlations between PBDE dust levels and residential characteristics (number of TVs and computers, floor area or flooring material) were observed. The daily intake of PBDEs via the inhalation pathway was estimated. House dust may be regarded as the most important exposure route of PBDEs for children.     

上海与伦敦城市绿地的生态功能及管理对策比较研究

在资料收集及实地采样调查的基础上 ,文章对上海与伦敦城市绿地的生态功能及管理对策进行了比较分析 ,指出了上海城市绿地建设及管理中的一些优点及不足之处。     

生物滤池对气相与液相中污染物质的净化

通过实验室研究探讨了生物滤池同时处理废水和废气的可行性。试验结果表明：在２５℃－３７℃条件下,甲苯废气的流量为９０Ｌ／ｈ,甲苯浓度为５００ｍｇ／ｍ＾３;废水的流量为０．４Ｌ／ｈ,ＣＯＤｃｒ浓度为４００－７５０ｍｇ／Ｌ,甲苯与ＣＯＤｃｒ的去除率分别是７０％－７２％和８６％－８９％。     

固定CO2氢细菌的筛选及其培养条件优化

从土壤中分离筛选到一株高效固定CO2 的氢氧化细菌—专性化能自养菌BHA 15 ,在最佳培养条件下(培养基 ρ/gL-1:NH4 Cl 4.0 ,Na2 HPO4 ·12H2 O 0 .75 ,KH2 PO4 0 .5 ,MgSO4 ·7H2 O 0 .3;V(H2 )∶V(O2 )∶V(CO2 ) =3 .5∶1∶1;pH =7;最适生长温度θ =30℃ ) ,密闭摇瓶中恒温 (30℃ )培养 40h后 ,菌体浓度 ρ(DW)达 1.6mg/mL ,菌体蛋白含量 71.8% .图 7表 2参 12     

碱性矿化水淋洗对土壤盐碱化及小麦生长的影响

为探讨不同矿化度的水对土壤盐渍化的影响及相应的淋洗分数,采用土柱模拟方法,以小麦为指示作物,设计1.0 g/L,1.5 g/L两种矿化度,按3750 m3/hm2灌溉量,分一水、二水两种灌次,秋后进行人工淡水淋洗。结果表明,在半干旱气候条件下,开发碱性矿化水灌溉矿化度不宜超过1.5 g/L,否则有引起碱化的危险。干旱期用碱性矿化水灌溉抗旱时,在同等灌水量的情况下,一水灌溉比二水灌溉积盐轻。各种人工淋洗处理比CK洗盐效果好,其中以等量淋洗综合效益最好。     

基于MODIS数据的安徽省植被水分利用效率时空变化及影响因素

水分利用效率是衡量生态系统碳水循环耦合程度的重要指标。基于MODIS数据、土地覆盖类型数据和气象数据,估算安徽省植被水分利用效率(WUE）,采用趋势分析法和相关分析法对安徽省2000~2014年植被WUE的时空格局、变化趋势及影响因素进行研究。研究表明:（1）不同植被类型的WUE年均值差异明显,常绿阔叶林和常绿针叶林的WUE均值较高,分别达到1.66和1.69 gC?mm-1?m-2,而耕地的年均WUE最低,各植被类型的年均WUE按照“常绿针叶林>常绿阔叶林>灌木>草地>落叶阔叶林>针阔混交林>耕地”的顺序递减。植被年均WUE具有较强的空间分异性规律,整体上呈现南北高中间低的趋势,植被WUE的高值区主要分布在大别山区和皖南山区,分布范围与常绿针叶林、常绿阔叶林的分布范围基本一致。（2）安徽省2000~2014年植被WUE年内变化呈现出“增加-减小-增加-减小”的M状“双峰型”趋势,具有明显的季节差异,呈现出春季＞秋季＞夏季＞冬季的特征,各季节植被WUE的均值分别占植被WUE的32.58%、24.91%、29.27%、13.24%。（3）安徽省植被WUE动态变化受到降水影响显著的区域占比3.88%;气温显著影响的区域占比2.19%;降水显著影响的地区主要分布在林地范围内,温度显著影响的地区则位于耕地范围内,降水和气温综合显著影响所占面积最小,为0.11%;而植被WUE受气温和降水影响均不显著占比为93.82%;整体上,安徽省大部分地区的植被WUE变化主要受非气候因素影响。     

清水冲涮对向家坝以下金沙江河床及岸线资源的影响

随着金沙江下游梯级水电开发的蓬勃开展,清水下泄对下游河床及岸线的影响问题逐渐显露。通过实地观测,走访及清水下泄前后政府和民间数据、影像资料等对比分析,探讨问题的根源和避免问题严重化途径,为共抓长江大保护,为修复长江生态环境提供参考依据。结果发现:清水下泄对向家坝水电站坝址以下金沙江段部分河床及岸线资源造成了较为明显的影响。如该江段原来常见的砂滩、砾石滩除杨湾码头仅存一个沙岛外,其余全部消失;无防护设施的河段(如火焰村小岸组、火焰组和新桥组,豆坝村的马槽、娱乐、黄泥、丰收、中心三组,普安镇的13、12、7、5、4、3、2、1组,西郊街道白石社区新村组)受顶冲作用导致一半以上河漫滩地流失甚至引起滩岸坍塌;白家滩大堤一处坝垛根石将被掏蚀殆尽。此外,水富港三期扩能工程因侵占河道和开挖船池,进一步加剧了对四川安边镇小岸坝的不利影响。严重的下蚀侧蚀导致该江段同期水位明显下降,也对岸线两侧的居民生产生活带来安全隐患。相关各方对区域的特殊性及水电站修建造成的影响存在认识不足,各自的发展、利益和环境保护需求之间的矛盾等是问题产生的根本原因,问题出现后又缺少有效的沟通机制等。     

Increasing the recovery of heavy metal ions using two microbial fuel cells operating in parallel with no power output

The present study aimed to improve the performance of microbial fuel cells (MFCs) by using an intermittent connection period without power output. Connecting two MFCs in parallel improved the voltage output of both MFCs until the voltage stabilized. Electric energy was accumulated in two MFCs containing heavy metal ions copper, zinc, and cadmium as electron acceptors by connection in parallel for several hours. The system was then switched to discharge mode with single MFCs with a 1000-Ω resistor connected between anode and cathode. This method successfully achieved highly efficient removal of heavy metal ions. Even when the anolyte was run in sequencing batch mode, the insufficient voltage and power needed to recover heavy metals from the cathode of MFCs can be complemented by the developed method. The average removal ratio of heavy metal ions in sequencing batch mode was 67 % after 10 h. When the discharge time was 20 h, the removal ratios of zinc, copper, and cadmium were 91.5, 86.7, and 83.57 %, respectively; the average removal ratio of these ions after 20 h was only 52.1 % for the control group. Therefore, the average removal efficiency of heavy metal ions increased by 1.75 times using the electrons stored from the bacteria under the open-circuit conditions in parallel mode. Electrochemical impedance data showed that the anode had lower solution resistance and polarization resistance in the parallel stage than as a single MFC, and capacitance increased with the length of time in parallel.

     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

基于安徽省土地利用变化的地形梯度效应分析

为揭示地形因素与土地利用空间格局演变的关系,以安徽省2000年、2005年以及2010年Landsat TM影像和DEM数据为数据源,利用坡向、地形起伏度、坡度变率和地形位指数多种地形因子,并结合地学信息图谱分析理论从综合角度系统研究土地利用结构时空分异格局在地形梯度上的变化特点及其规律。结果表明:1)研究区主要的土地利用类型是耕地和林地,其次是建设用地和未利用土地,且建设用地面积逐期增加趋势显著。2)2000~2010年研究区不同土地利用类型在不同地形梯度区间的分异规律存在明显差异。低地形梯度范围是耕地、水域和建设用地的优势分布区;中地形梯度范围是草地的集中分布区;林地的优势分布区集中在高地形梯度范围。3)2000~2010年研究区土地利用图谱以稳定型和后期变化型为主,低地形梯度和高地形梯度是稳定型图谱的集中分布区,中低、中高和高地形梯度范围是后期变化型图谱的优势分布区。2000~2005年林地的优势分布区有向较低地形位梯度扩张的趋势,其中,耕地是主要的转入来源。2005~2010年耕地的优势分布区有向较高地形位梯度扩张的趋势,变化模式主要为:"林地–耕地"、"未利用地–耕地"和"草地–耕地"。