Estimates of daily oxygen consumption,carbon dioxide and methane emissions,and heat production for beef and dairy cattle using spot gas sampling

A simulation study was conducted to examine accuracy of estimating daily O₂ consumption, CO₂ and CH₄ emissions, and heat production (HP) using a spot sampling technique and to determine optimal spot sampling frequency (FQ). Data were obtained from 3 experiments where daily O₂ consumption, emissions of CO₂ and CH₄, and HP were measured using indirect calorimetry (respiration chamber or headbox system). Experiment 1 used 8 beef heifers (ad libitum feeding; gaseous exchanges measured every 30 min over 3 d in respiration chambers); Experiment 2 used 56 lactating Holstein-Friesian cows (restricted feeding; gaseous exchanges measured every 12 min over 3 d in respiration chambers); Experiment 3 used 12 lactating Jersey cows (ad libitum feeding; gaseous exchanges measured every hour for 1 d using headbox style chambers). Within experiment, averages of all measurements (FQALL) and averages of measurements selected at time points with 12, 8, 6, or 4 spot sampling FQ (i.e., sampling every 2, 3, 4, and 6 h in a 24-h cycle, respectively; FQ12, FQ8, FQ6, and FQ4, respectively) were compared. Within study a mixed model was used to compare gaseous exchanges and HP among FQALL, FQ12, FQ8, FQ6, and FQ4, and an interaction of dietary treatment by FQ was examined. A regression model was used to evaluate accuracy of spot sampling within study [i.e., FQALL (observed) vs. FQ12, FQ8, FQ6, or FQ4 (estimated)]. No interaction of diet by FQ was observed for any variables except for CH₄ production in experiment 1. No FQ effect was observed for gaseous exchanges and HP except in experiment 2 where CO₂ production was less (5,411 vs. 5,563 L/d) for FQ4 compared with FQALL, FQ12, and FQ8. A regression analysis between FQALL and each FQ within study showed that slopes and intercepts became farther from 1 and 0, respectively, for almost all variables as FQ decreased. Most variables for FQ12 and FQ8 had root mean square prediction error (RMSPE) less than 10% of the mean and concordance correlation coefficient (CCC) greater than 0.80, and RMSPE increased and CCC decreased as FQ decreased. When a regression analysis was conducted with combined data from the 3 experiments (mixed model with study as a random effect), results agreed with those from the analysis for the individual studies. Prediction errors increased and CCC decreased as FQ decreased. Generally, all the estimates from FQ12, FQ8, FQ6, and FQ4 had RMSPE less than 10% of the means and CCC greater than 0.90 except for FQ6 and FQ4 for O₂ consumption and CH₄ production. In conclusion, the spot sampling simulation with 3 indirect calorimetry experiments indicated that FQ of at least 8 samples (every 3 h in a 24-h cycle) was required to estimate daily O₂ consumption, CO₂ and CH₄ production, and HP and to detect changes in those in response to dietary treatments. This sampling FQ may be considered when using techniques that measure spot gas exchanges such as the GreenFeed and face mask systems.     

Reducing numerical dissipation in smoke simulation

Numerical dissipation acts as artificial viscosity to make smoke viscous. Reducing numerical dissipation is able to recover visual details smeared out by the numerical dissipation. Great efforts have been devoted to suppress the numerical dissipation in smoke simulation in the past few years. In this paper we investigate methods of combating the numerical dissipation. We describe visual consequences of the numerical dissipation and explore sources that introduce the numerical dissipation into course of smoke simulation. Methods are investigated from various aspects including grid variation, high-order advection, sub-grid compensation, invariant conservation, and particle-based improvement, followed by discussion and comparison in terms of visual quality, computational overhead, ease of implementation, adaptivity, and scalability, which leads to their different applicability to various application scenarios.     

以IBAC为核心处理洗浴废水的试验研究

根据洗浴废水的水质特征,采用原水→混凝沉淀-过滤→固定化生物活性炭(Immobilized Biological Activated Carbon,IBAC)→微滤膜(MF)→UV消毒→出水的工艺流程.混凝沉淀-过滤物化预处理单元可以有效地减少洗浴废水中的各类污染物.IBAC生化处理单元,实现有机污染物、LAS、浴臭等有效去除,是保证出水合格的根本措施.微滤膜发挥物理截留作用、UV消毒杀死细菌和总大肠菌群.出水水质达到＜城市供水水质标准＞(CJ/T 206-2005).     

地下水污染试验研究进展

本文在总结国内外众多学者有关污染物在含水层中的运移规律研究成果的基础上，介绍了地下水污染试验研究的最新进展；并据此认为，三维弥散，各向异性含水层介质中污染物的迁移，非饱和土层中的污染物多相迁移和吸力的关系等将成为今后地下水污染传播研究的主要问题。     

汽车代用燃料的应用和发展

评述了汽车代用燃料的现状和未来，压缩天然气和液化石油气将率先大量使用，其次是醇燃料，合成燃料和二甲醚将主要用于某些混合动力车，燃料电池因为能源效率高是最有吸引力的车用能源，将于2010-2015年开始在汽车上实际使用，我国石油工业在提升汽油和柴油质量的同时，应与汽车工业联手开发代用燃料，特别要注意发展燃料电池技术。     

海洋石油开发工业污染物产生系数和排放系数研究

污染物产生系数和排放系数是工程环境影响评价的重要指标,但对于海洋石油开发工程环境影响评价来说,迄今尚无具权威性的系数可资使用。在我国近海石油开发工程污染源系统调查的基础上,对海洋石油开发行业污染物产生系数和排放系数的定义、计算方法、应用范围及应用方式进行了探讨,研究结果可为海洋石油开发工程项目环境影响评价及环境保护管理,以及行业或企业有关标准的制定提供参考。     

波流环境中污染物混合的分析

本文根据垂向二维数值模型计算求解和分析了波流环境中的一维对流扩散方程中的混合系数。此二维数值模型采用非线性k-ε紊流模型封闭雷诺时均方程，应用VOF方法处理自由面。分析方法是用该二维模型计算波流环境中污染物瞬时源产生的浓度场，计算该浓度场的断面平均浓度，求此断面平均浓度的概率分布，由概率分布的方差随时间的导数得到一维对流扩散问题中的混合系数。通过算例分析，发现波流环境混合系数随着波浪周期和波 高的不同，可能大于纯流和纯波的混合系数之和，也可能比纯流情况下小；波周期与混合系数呈正比。且存在一个使混合系数最大的波高。     

燃气红外线辐射器的节能与环保特性分析

论述了燃气红外线辐射器的基本原理 ,对其节能与环保特性的分析表明 :与大气式燃烧器相比 ,红外线辐射器的燃料节约率为 15 %～ 45 % ,CO2 排放量减少率为 15 %～ 48% ,CO排放量减少率为 96.2 %～ 97.7% ,NOx 减少率为 94.9%～ 96.9% ,具有显著的节能与环保效果     

催化燃烧炉的节能性分析

传统的火焰燃气炉往往会产生不同数量的氮氧化物(NO和NO2)、一氧化碳等不完全燃烧产物,造成了环境污染和能源浪费.催化燃烧作为一种新的燃烧方式,打破了传统火焰燃烧的可燃界限,实现了贫甲烷/空气混合物在可燃界限以下的燃烧,燃烧效率高,提高了能源利用率.将催化燃烧应用于燃气炉,可以解决燃气炉由于火焰燃烧带来的燃烧效率低等缺点,达到节约能源的目的.以催化燃烧和燃气炉为依据,在催化燃烧炉Ⅰ型的基础上研制出催化燃烧炉Ⅱ型,分析了催化燃烧炉的热损失以及热效率,并与传统火焰燃烧炉做了比较.结果表明,催化燃烧炉Ⅱ型的热损失并不大,热效率较高,且其污染物排放量极低.