炼油厂酸性水汽提装置存在的问题及对策

目前炼油厂酸性水汽提装置存在着诸如汽提净化水中氨含量过高、侧线抽出富氨气中硫化氢含量过高、汽提塔处理能力达不到设计负荷等问题。通过分析，提出了相应的改进对策，如加碱汽提、流程优化等。     

冷却塔噪声治理途径

本文综述了冷却塔噪声治理的主要进展。通过对冷却塔噪声的分析，提出了冷却塔噪声治理的途径。     

爆破拆除高耸建筑物触地危害分析与控制

分析爆破拆除高耸建筑物倒塌触地产生的危害:触地震动、触地飞石和超压气流。基于一般塌落质点振动速度公式,提出3种减少震动危害的措施;根据抛体运动规律,得出触地飞石水平飞行范围,提出3种减少触地飞石危害的措施;在分析超压气流危害机理的基础上,提出了3种减少超压气流危害的措施。并引用实例进行分析说明。     

过程液氯贮槽装置封闭厂房及事故氯吸收塔联用安全效用分析

分析、设立液氯贮槽液相泄漏的几种典型事故情景,并利用液相泄漏、液池蒸发、重气扩散和人员中毒死亡概率等模型对比研究封闭厂房及事故氯吸收塔等安全措施对液氯贮槽液相泄漏扩散中毒后果的影响,给出不同事故情景下液氯泄漏速率、液池半径、液池蒸发速率、室外氯气中毒死亡概率等事故后果特征值。对封闭厂房及事故氯吸收塔安全效用进行定量分析和比较研究。结果表明,液氯贮槽的封闭厂房对抑制液氯泄漏扩散中毒事故后果效用明显;事故氯吸收塔能消除液氯贮槽微小孔泄漏所对应的小事故情景,还能对封闭厂房最严重泄漏事故后果起到初期削峰作用。显然,封闭厂房及事故氯吸收塔联用可以降低液氯贮槽事故影响后果,具有良好安全效用。     

百色市中波台对塔吊感应高压电的影响及防护研究

电磁辐射主要通过感应耦合或电磁耦合使主要由金属部件组成的塔吊感应高压电,而塔吊的结构及架设常使其更容易遭受电磁辐射的影响,特别是有中波发射塔存在的区域电磁辐射水平较高,对塔吊的影响较为明显,从而危及施工人员和财产安全。针对百色市二四二中波发射台的电磁辐射状况,通过对电磁射源及电磁环境特点等方面进行分析与计算,利用等效电路模型探讨电磁辐射对附近施工建筑塔吊感应高压电的影响,得出塔吊的谐振点、中波发射台在塔吊处的电场强度及感应电压。采取绝缘、重复接地和避开谐振点方法解决长期以来建筑塔吊临近通讯发射源感应高压电而难于防护的突出问题,从而提高塔吊在电磁辐射环境中工作的安全性,并对此类领域的研究或对类似感应电的防护提供科学借鉴。     

特大型冷却塔及冷水机组房噪声治理

本文对特大型冷却塔及冷水机组房的噪声特性进行了测量分析。根据其噪声源特性，采取了加装进排气消音器、吸声、隔声、减振等综合治理方案。治理后的实测结果表明：该项噪声治理工程投资少，达到标准的要求。     

麦草制浆黑液对燃煤烟气同时脱硫除汞性能研究

本文利用多级水幕吸收塔,研究了循环液气比(L/G)、空塔气速、进口烟气SO2浓度以及进口烟气Hg浓度对麦草制浆黑液脱硫除汞效果的影响.实验结果表明:随着L/G增加、空塔气速增大、进口SO2浓度降低,脱硫除汞效果得到了不同程度的提升;随着进口Hg浓度升高,脱汞效率缓慢下降,脱硫效率基本不变.通过提高L/G、增加空塔气速、降低进口SO2浓度与Hg浓度提麦草制浆黑液高脱硫除汞效率,为麦草制浆黑液协同脱硫除汞奠定应用基础.     

稳定塔安全阀起跳原因分析及对策

当工艺操作参数波动较大时,尤其是在开工阶段,杨易造成稳定塔安全阀起跳.分析了安全阀起跳的原因,认为主要原因是稳定塔负荷过大及稳定塔塔顶温度过高,提出了相应的预防安全阀起跳的工艺控制措施.     

玻璃建材厂含氟废气处理工程实践

采用旋流板塔处理含氟废气，氟化物平均浓度从１０８５ｍｇ／Ｎｍ３降至７５ｍｇ／Ｎｍ３，二氧化硫从７９５５ｍｇ／Ｎｍ３降至１２６３ｍｇ／Ｎｍ３，平均去除率氟化物为９３％，二氧化硫８４１％     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.