氨氮对反硝化型甲烷厌氧氧化细菌的影响机理研究

反硝化型甲烷厌氧氧化(Denitrifying Anaerobic Methane Oxidation,DAMO)是以甲烷为电子供体和唯一碳源,以硝酸盐或亚硝酸盐为电子受体的一种氧化还原反应,可用于废水脱氮,而氨氮是含氮废水中存在的主要形式.目前的研究认为主导DAMO过程的微生物主要有DAMO细菌和DAMO古菌.本文以DAMO细菌为优势菌种的系统为研究对象,通过短期和长期试验,从宏观和微观上研究了氨氮对该系统短期和长期的影响,并比较了不同pH体系下影响效果差异,揭示了相关影响机理.短期试验研究表明,氨氮对该系统的安全浓度为250 mg·L~(-1).当氨氮浓度为500 mg·L~(-1)时,对该系统的脱氮效率造成明显的抑制作用,并且随着浓度、时间的增加,氨氮对其的抑制效果增强;不同pH条件下抑制效果的差异对比发现,在碱性条件下,真正起抑制作用的是氨氮的质子化形式FA(Free Ammonia),在中性及酸性条件下,真正起抑制作用的抑制因子是离子化的NH_4~+.通过扫描电镜对系统中絮状污泥分析发现,在氨氮的短期抑制后,系统内的微生物出现了明显皱缩,丝状菌的数量增加;采用高通量测序技术分析了长期氨氮抑制后的系统,结果显示,系统内菌群结构发生较大改变,物种的多样性和丰度都大大降低.通过菌属分析认为,系统脱氮效率的降低是由于Methylomonas(甲基单胞菌属)数量的减少引起的.     

冰雹天气的短时监测预报及消雹作业评估

本文研制的冰雹短时监测预报方法综合利用了T-lnP、天气图和雷达回波等资料,它把本地的降雹机制转化成对流的发生、发展、触发三指数,作为一级预报;通过计算T-lnP图上有关冰雹的层结指数,判断出冰雹强度,作为二级预报;利用雷达回波指标作为三级预报,以实现冰雹灾害天气的定时、定点、定量预报.同时对1996～2002年本地开展的人工消雹情况进行了效益评估.     

Accuracy improvement of various short-term load forecasting models by a novel and unified statistical data-filtering method

ABSTRACT

Time-series and machine-learning methods are being strongly exploited to improve the accuracy of short-term load forecasting (STLF) results. In developing countries, power consumption behaviors could be suddenly changed by different customers, e.g. industrial customers, residential customers, so the load-demand dataset is often unstable. Therefore, reliability assessment of the load-demand dataset is obviously necessary for STLF models. Hence, this paper proposes a novel and unified statistical data-filtering method with the best confidence interval to eliminate unexpected noises/outliers of the input dataset before performing various short-term load forecasting models. This proposed novel data-filtering method, so-called the data pre-processing method, is also compared to other existing data-filtering methods (e.g. Kalman filter, Density-Based Spatial Clustering of Applications with Noise, Wavelet transform, and Singular Spectrum Analysis). By using an SCADA system?-based database of a typical 22kV distribution network in Vietnam, NYISO database, and PJM-RTO database, case studies of short-term load forecasting have been conducted with a conventional ARIMA model, an ANN forecasting model, an LSTM-RNN model, an LSTM-CNN combined model, a deep auto-encoder (DAE) network, a Wavenet-based model, a Wavenet and LSTM hybrid model, and a Wavelet Neural Network (WNN) model, which are to validate the novel and unified statistical data-filtering method proposed. The achieved numerical results demonstrate which the accuracy of the aforementioned STLF models can be significantly improved due to the proposed statistical data-filtering method with the best confidence interval of the input load dataset. The proposed statistical data-filtering method can considerably outperform the existing data-filtering methods.     

2001年11月14日昆仑山口西8.1级大震前徐州台数字化形变观测仪器记录的异常

北京时间 2 0 0 11114T 17∶2 6 ,在昆仑山口西发生了 8 1级地震。震中为 36 2°N ,90 9°E。这次地震前徐州地震台体应变仪、水管仪、伸缩仪数字化形变观测记录到了较明显的短临异常信息。本文试对这些异常进行分析。     

鱼类和两栖类胚胎幼体慢性毒性短期试验

采用鲤鱼和黑斑蛙进行了丙烯腈、乙腈、硫氰酸钠和二甲基甲酰胺等４种污染物的鱼类和两栖类胚胎幼体毒性试验．结果表明，４种污染物对鲤鱼的慢性毒性值分别为２．２６、５５６、２８．３和１１３１ｍｇ／Ｌ，已腈、硫氰酸钠和二甲基甲酰胺对黑斑蛙的慢性毒性值分别为２８２８、５６．５和４５２５ｍｇ／Ｌ，说明采用胚胎幼体试验能够有效地预测污染物的慢性毒性效应．     

地方政府短期行为对环境管理的制约及其对策

经济体制转型期,地方政府的短期行为为给基层环境管理带来一系列负面影响,这是造成目前地方环境问题的重要因素之一。这个问题的存在,有思想、体制、管理、监督诸方面的原困,必须相应采取措施防止和克服地方政府短期行为对环境管理的制约。     

Evolution,variability and sustainable development

SUMMARY

Sustainable development is a global challenge to science and society. In politics and economics the concepts for establishing a sustainable society are numerous, nonetheless necessary interdisciplinary approaches are still marginalised. Trying to foster a deeper communication between biology and social science, an evolutionary perspective on sustainable development is offered. Subsequently, the role of variability and diversity in evolution is highlighted. Hereby, special attention is devoted, among other things, to the links between variability and stability in the long term. Next, selection and variability are emphasised in the cultural context. This is followed by general implications for sustainability. In contrast to strategies aiming at short-term optimisation and economic efficiency, we argue that the conditions and circumstances maintaining variability and momentary sub-optimal alternatives are highly relevant for a socio-economic system that is heading for sustainable development.     

基于多因素的LSTM瓦斯浓度预测模型*

为解决煤矿瓦斯浓度预测问题,提出基于多因素的LSTM瓦斯浓度预测模型。模型首先对煤矿多源监测数据进行数据融合、缺失值处理;其次通过特征衍生、有监督化、无量纲化,融合各环境因素特征和时序数据的时间性特征,且衍生出更多交叉项特征和高次项特征;然后利用经验法和逐步试错法确定隐藏层维度;最后进行模型训练和测试。研究结果表明:基于多因素的LSTM瓦斯浓度预测模型的RMSE仅为0.021,MAE为0.01,比单因素LSTM模型、RNN模型预测效果好。因此,基于多因素的LSTM瓦斯浓度预测模型可更精准地进行瓦斯浓度多步预测,促进煤矿安全生产。     

间伐对马尾松人工林林下植物多样性的短期和长期影响

探讨不同间伐强度林下马尾松人工林植物多样性的动态变化,为确定合理的间伐强度提供理论依据。以南京溧水林场马尾松俨砌USmassonianaLamb．）中龄人工林为研究对象,于2007年和2011年对间伐1a和5a后各间伐林下植物多样性进行了调查和分析。结果表明：间伐la和5a后,与对照相比,中强度间伐林下植物种类、数量、丰富度Margalef指数、多样性Simpson、Sharmon-Weiner指数和均匀度JSW指数均显著提高（P〈O．05）,林下植物的生态优势度指数显著降低（P〈O．05）;弱度间伐林下各指数在间伐1a后显著降低（P〈O．05）,而在间伐5a后显著提高（P〈O．05o中强度间伐后林分各指数增幅最大,其中Shannon．Wiener指数对间伐措施更为敏感。间伐5a后,中强度间伐林下植物种类、数量和多样性指数比间伐1a后有所提高,弱度、中度、强度间伐后的林下植物种类比对照分别增加15、17和15种,总密度分别增加1．40、3．44和2．14倍。从短期和长期影响效果来看,中、强度间伐有利于植物多样性的提高。     

水质自动监测系统在厦门同安湾赤潮短期预报中的应用

利用2005年同安湾水质在线自动监测系统的数据,分析了同安湾赤潮前和赤潮中的实时在线监测资料,并与相关资料进行比对。初步建立数理统计预报和经验预报两种预报模式,进行同安湾2种藻类(中肋骨条藻、旋链角毛藻)赤潮短期预报。研究结果初步表明,可提前1~3 d对同安湾的中肋骨条藻或旋链角毛藻赤潮进行预警。同安湾在线监测的赤潮预警值初步定为:溶解氧饱和度105%、叶绿素8.0μg/dm3。