1万Kva电石炉烟气的治理

介绍遵义碱厂红果化工分厂采用强制风冷器 LMC低压长袋脉冲除尘器净化1万 kVA电石炉烟气的技术.     

新型高效反硝化除磷工艺

针对传统生物脱氮除磷工艺中存在的问题,简述了反硝化除磷工艺所具有的优点及其代谢途径．提出了两种典型的反硝化除磷工艺,并介绍了反硝化除磷技术的影响因素和测定方法。反硝化除磷技术的应用可解决传统生物脱氮除磷工艺中硝化菌污泥龄与聚磷菌污泥龄的差别以及反硝化菌与聚磷菌之间有机物之争的难题。     

试论环境空气质量自动监测系统的设计

目前 ,我国重点城市都在开展环境空气质量日报或预报工作 ,开展这一工作的基本条件之一是必须建立环境空气质量自动监测系统。由于我国目前的研制水平有限 ,空气质量自动监测系统基本上是靠引进国外技术及设备来完成的。而引进设备往往与我国的具体实际结合不够 ,尤其是在系统结构、数据采集、远程控制与诊断方面同我们的实际要求相去甚远。为此本文将围绕国内环境监测共同关注的环境空气质量自动监测系统及其设计的问题展开讨论 ,内容包括目前国内自动监测系统的现状 ;国外发展情况及趋势 ;自动监测系统结构与要求     

大跨度偏压隧道受火损伤分析

为探明火灾对大跨度偏压隧道造成的不利影响,依托贵州省某公路隧道工程,基于ANSYS有限元软件分析不同埋深及偏压条件下大跨度隧道结构的最大损伤和相对温度损伤变化规律,并对其温度场分布和应力分布规律进行总结。结果表明:衬砌高温损伤约60 mm,温度影响深度约300 mm,内部温升过程逐渐由曲线变化转变为直线变化;最大损伤深度随偏压角度增加近似呈指数增长变化,而相对温度损伤略有减小,当偏压角度较大时,火灾将成为隧道破坏的诱导因素而非直接因素;最大损伤深度与偏压隧道埋深近似呈抛物线变化,火灾对偏压隧道影响显著,必须采取有效预防措施;随着受火时间的增加,临火侧衬砌混凝土在热膨胀及围岩约束作用下,压应力快速增加,存在较大的压溃风险。     

Long-term thermophilic mono-digestion of rendering wastes and co-digestion with potato pulp

In this study, mono-digestion of rendering wastes and co-digestion of rendering wastes with potato pulp were studied for the first time in continuous stirred tank reactor (CSTR) experiments at 55 °C. Rendering wastes have high protein and lipid contents and are considered good substrates for methane production. However, accumulation of digestion intermediate products viz., volatile fatty acids (VFAs), long chain fatty acids (LCFAs) and ammonia nitrogen (NH₄-N and/or free NH₃) can cause process imbalance during the digestion. Mono-digestion of rendering wastes at an organic loading rate (OLR) of 1.5 kg volatile solids (VS)/m³ d and hydraulic retention time (HRT) of 50 d was unstable and resulted in methane yields of 450 dm³/kg VS_fed. On the other hand, co-digestion of rendering wastes with potato pulp (60% wet weight, WW) at the same OLR and HRT improved the process stability and increased methane yields (500–680 dm³/kg VS_fed). Thus, it can be concluded that co-digestion of rendering wastes with potato pulp could improve the process stability and methane yields from these difficult to treat industrial waste materials.     

Application of an early warning indicator and CaO to maximize the time–space-yield of an completely mixed waste digester using rape seed oil as co-substrate

In order to increase the organic loading rate (OLR) and hereby the performance of biogas plants an early warning indicator (EWI-VFA/Ca) was applied in a laboratory-scale biogas digester to control process stability and to steer additive dosing. As soon as the EWI-VFA/Ca indicated the change from stable to instable process conditions, calcium oxide was charged as a countermeasure to raise the pH and to bind long-chain fatty acids (LCFAs) by formation of aggregates. An interval of eight days between two increases of the OLR, which corresponded to 38% of the hydraulic residence time (HRT), was sufficient for process adaptation. An OLR increase by a factor of three within six weeks was successfully used for biogas production. The OLR was increased to 9.5 kg volatile solids (VS) m^?3 d^?1 with up to 87% of fat. The high loading rates affected neither the microbial community negatively nor the biogas production process. Despite the increase of the organic load to high rates, methane production yielded almost its optimum, amounting to 0.9 m³ (kg VS)^?1. Beneath several uncharacterized members of the phylum Firmicutes mostly belonging to the family Clostridiaceae, a Syntrophomonas-like organism was identified that is known to live in a syntrophic relationship to methanogenic archaea. Within the methanogenic group, microorganisms affiliated to Methanosarcina, Methanoculleus and Methanobacterium dominated the community.     

长期低温对絮状-颗粒耦合CANON脱氮及菌群影响

在SBR反应器中探究长期低温对等污泥浓度比例絮状-颗粒(1:1～1:1.5)耦合CANON系统的脱氮效能和微生物群落结构的影响.结果表明,在经历长期低温(10℃)条件下运行并回温(10→30℃)后,等比例污泥CANON系统NH₄⁺-N、TN去除率及TN去除负荷与温度变化呈正相关性,在回温30℃下运行30d后分别达到72.4%、63.0%和0.094kgN/(m³·d).氨氧化菌(AOB)和厌氧氨氧化菌(AAOB)活性与温度表现出正相关性,在回温后分别为0.025和0.049gN/(gVSS·d),分别为降温前(30℃)的83.3%和79.1%,NOB活性一直维持在较低水平(0.001gN/(gVSS·d)).高通量测序结果显示,长期低温对优势菌门无明显影响.回温后,颗粒和絮状污泥中的优势菌门分别为Ignavibacteriae和Proteobacteria;回温后系统颗粒污泥中功能菌Candidatus Brocadia、Candidatus Kuenenia(AAOB)相对丰度分别为6.017%、2.623%,其在絮状...     

基于MSLSTM-DA模型的水质自动监测异常数据报警

提出一种基于多元堆叠长短时记忆网络-差值分析(MSLSTM-DA)模型对地表水质异常数据进行报警的方法.该方法首先建立MSLSTM模型对水质指标数据进行预测,再基于预测结果的残差分布建立DA模型,并确定各个指标的数据异常阈值,当实测数据与预测数据差值大于阈值时进行数据报警.以长江流域监测断面的水质数据进行了方法有效性验证.结果表明,构建的预测模型对５个指标的MAE、MAPE均值比BP神经网络预测模型降低21.0%,17.8%,比LSTM模型降低16.8%,17.9%.皮尔逊系数均值比BP神经网络、LSTM模型的分别高5.9%,4.4%.5个指标共检出水质异常数据37条,其中34条经人工判断确实存在有异常,报警准确率高达91.9%.