城市固体废物生物处理方法及其可行性

生物反应堆是通过强化微生物转化和降解有机废物的能力进行处理固体废物的一种方法。本文分别对好氧生物处理、厌氧生物处理和兼性生物处理的机理、影响因素以及各污染物质的迁移转化规律进行综合分析。研究表明生物反应堆具有明显的社会、环境、经济效益,是实现可持续发展的一条重要途径,为以后的研究和应用提供可靠的理论依据。     

利用氨水对液体烟幕残留物自净化的方法

针对军事上大量使用的液体烟幕的残留物所存在的严重污染问题,研究了利用氨水的自净化法。探讨了自净化的机理和氨水的不同浓度、不同用量对净化效果的影响。该方法简单、高效,既可保持烟幕本身的功用特性,又可解决其残留物的严重污染问题,具有重要的环保价值,也是在军事运用中强调环保的一种有益尝试。     

模糊线性规划在灾害对策中的应用

本文把模糊线性规划方法引入灾害对策的研究当中。着重讨论了疏散人口和疏散地点间的关系,简单介绍了模糊疏散距离及其初步确定方法。     

建筑小区的海绵化改造效益核算——以固原市玫瑰苑小区为例

以固原市玫瑰苑小区为例,根据小区可改造绿地空间充足、雨落管断接改造难度较小等特点,提出了海绵化改造思路及工程内容,并对海绵化改造后的经济效益和生态效益进行核算。结果表明:通过海绵化改造即改造排水系统,建设下沉式绿地、植草沟、雨水花园、雨水罐、蓄水池、透水铺装等措施,可使小区综合雨量径流系数降低0.21,小区雨水径流量减少5 137.85 m ³∕a,具有良好的雨水调蓄效益;海绵化改造后具有一定的经济效益,可节约城市排水设施费用411.03元∕a,节约自来水费用4 159.20元∕a,节水效益达28 155.42元∕a;海绵化改造后可吸碳8.18 t∕a,释放氧气6.31 t∕a,吸收二氧化硫50.73 kg∕a,生态环境效益显著。     

蔬菜类废弃物甲烷发酵的产气潜能及过程特征

蔬菜废弃物具有适合厌氧发酵的特性。采用Batch实验方法,对5种常见的蔬菜废弃物的产气潜能进行研究,并在此基础上进一步对厌氧发酵过程限制性步骤及物质转化特征进行分析。研究结果表明:5种蔬菜废弃物累积产甲烷量在发酵0～10 d内增加较快,土豆和白菜废弃物产甲烷潜能最大,分别达到102 mL·g-1(VS),和83 mL·g-1(VS),而黄瓜废弃物的甲烷化潜能较低,只有35 mL·g-1(VS)左右。动力学参数拟合表明:土豆和白菜废弃物厌氧发酵水解、酸化、乙酸化和甲烷化各过程转化速率都明显高于其他废弃物,并且各过程最大转化潜能也较其他类蔬菜高出2倍之多。厌氧发酵限制性步骤分析表明,快速水解生成的SCOD不能有效地转化为VFAs,限制了白菜废弃物厌氧消化的后续转化,而VFAs的累积则是胡萝卜、黄瓜和土豆废弃物厌氧发酵的限制性步骤, SCOD以及VFAs同时累积是茄子废弃物发酵过程的显著特征。对各物质发酵过程物质转化特征分析表明,各废弃物由于4 d以后甲烷菌对乙酸的利用减慢,导致丙酸向乙酸的转化减慢而发生累积现象,10 d以后由于产酸过程的减弱,累积的丙酸盐逐渐转化。     

城市污水处理过程中不同形态氮类营养物的转化特性

针对不同形态氮类营养物在城市污水处理系统中迁移转化机理尚不明确这一问题,通过现场监测和实验室模拟分析,研究不同形态氮类营养物在整个城市污水处理系统(A/A/O工艺)中的转化特性。研究结果表明,在原污水总氮中溶解态氮和颗粒态氮比例相当,浓度分别为39.28 mg/L和41.24 mg/L,无机氮是溶解态氮的主要成分,比例占93.2%(36.61 mg/L),而有机氮含量极少,仅为2.67 mg/L。在颗粒态氮中有机氮比重很大,约占96.58 %(39.83 mg/L)。在整个一级处理过程中溶解态氮变化量很小,而颗粒态有机氮减少了45%,总氮降低主要是由于颗粒态有机氮通过沉淀作用去除而实现的。现场监测和模拟实验结果表明,溶解性有机氮在厌氧区和缺氧区中由于被厌氧微生物降解而大幅度减少,而在好氧区却有一定程度的增加。二级出水中的氮主要还是以无机氮为主,可通过进一步优化工艺参数来强化系统硝化/反硝化作用,去除污水中残留的无机氮。     

感应电动势与参照系的相对关系

本文从电磁场变换入手,举例说明感应电动势的大小及区分感生、动生电动势与参照系有关.     

ECONOMIC ANALYSIS OF IRRIGATION PRODUCTION FUNCTIONS: AN APPLICATION OF LINEAR PROGRAMMING1

ABSTRACT: Economic analysis of irrigation production functions is discussed using linear programming. The method provides advantages over the partial one-crop type of analyses because it captures intercrop tradeoffs in water and land use in response to economic policies or changes in water supply. A numerical example is used.     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.