光合细菌和螺旋藻对黄泔水净化与利用初探

应用光合细菌将黄泔水中的有机物降解转化为无机氮磷后养殖螺旋藻。结果表明,在实验条件下光合细菌对黄泔水ＣＯＤｃｒ的去除率可达７０％,处理后的黄泔水用甲壳质絮凝澄清后加入螺旋藻并曝气进行培养,藻生长周期为２２ｄ,生长速率为２０－３０ｍｇ／Ｌ．Ｄ。藻体蛋白质含量平均为５２．６ｇ／１００ｇ游离氨基酸平均含量为２．４ｇ／１００ｇ。     

封闭式存贮塘处理采油污水的可行性研究

针对石西油田的区域特点,从工程设计、气象、地质、投资等多方面对该地区利用封闭式存贮塘处理采油的可行性进行了分析研究,提出该法可作为相似地区油田采油废水处理方法借鉴的观点      

LFG控制利用工程基本参数的试验研究

通过深圳市玉龙坑垃圾填埋场的现场抽气试验。本文进行了填埋气本安全控制与回收利用工程基本参数的研究。     

城市生活垃圾处理利用生态工程技术

城市垃圾处置是城市环境管理中的一大难题。后工业化国家普遍采用的末端治理技术不适合我国国情。运用生态工程技术,将城市垃圾处理与利用相结合,寓处理于利用之中,寓环境保护于产业生产之中,发展垃圾处理利用生态产业是解决这一难题的可由之路。在广汉市的研究与探索表明：通过硬件、软件、心件的结合,政府引导、科技支持、企业经营、居民参与,使城市垃圾减量化、无害化、资源化,处理利用产业化、系统化,可以达到环境效益与经济效益、社会效益的统一。论述了城市垃圾处理利用生态工程的原理及具体措施与设计     

香港城市固体废物系统管理

本文以大量翔实的数据介绍了香港对城市固体废物的系统管理,即分类、收集、监测分析、处理和预测评价。香港环保署自８０ 年代开始对城市固体废物进行监测并系统管理。在全港设置了３ 个大型策略性填埋场、５ 个垃圾转运站、１ 个垃圾焚烧厂（１９９７ 年５ 月关闭） 和１个化学废物处理中心。目前,香港政府正筹建一个新的、技术先进的焚烧厂。从１９８６ ～１９９７年,这些废物处理设施处理全港废物量为８９６０ ～２４３００ｔ／ｄ,其中城市固体废物比例每年不等,最低为３０ ．７ ％ ,最高为６５ ．５ ％ 。１９９７ 年,这些废物中可循环再利用物接近５０ ％ ,出口部分达１２０ 多万吨,回收资金２０ 多亿港元。根据历年来城市固体废物量与本地生产总值（ＧＤＰ）和人口数量的密切相关性,预测出２０１１ 年城市固体废物人均产率为２ ．５６ｋｇ／ 人·ｄ, 城市固体废物量为１２８１０ ｔ／ｄ。城市固体废物系统管理紧迫而重要,香港的经验是值得我们借鉴的。     

用氟化钾水溶液从制药废液中回收吡啶

研究了普通精馏与加盐分相技术在回收吡啶中的应用。测定了吡啶 水 氟化钾体系在25℃时的液液相平衡数据,采用Pitzer理论和UNIQUAC方程对相平衡数据进行了理论计算,结果表明计算值与实验值符合良好。采用氟化钾水溶液回收吡啶,当60%氟化钾浓溶液与50%吡啶/50%水的物料的质量比为2.0时,有机相中吡啶的纯度可达到92.60%(质量分数),水相中氟化钾稀溶液经蒸发回收后循环使用不影响分离性能。该工艺的开发成功为制药行业从制药废液中回收吡啶开辟了一条新途径。     

处理乙硫醇废气生物滤池中微生物的初步鉴定

生物滤池是废气生物处理的主要技术之一 ,其生物相包括细菌和真菌 .对于疏水性有机物质 ,真菌具有更高的处理效率 ,而且真菌对环境的适应性也比细菌强 .本研究采用生物滤池处理含乙硫醇废气 ,通过对生物滤池填料上附着的微生物进行分离鉴定表明 ,初步判定分离出的菌株分别为常现青霉、宛氏拟青霉、文氏曲霉和顶孢头孢霉 .     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

The role of lipids in fermentative propionate production from the co-fermentation of lipid and food waste

● Lipid can promote PA production on a target from food waste. ● PA productivity reached 6.23 g/(L∙d) from co-fermentation of lipid and food waste. ● Lipid promoted the hydrolysis and utilization of protein in food waste. ● Prevotella , Veillonella and norank _f _Propioni bacteriaceae were enriched. ● Main pathway of PA production was the succinate pathway. Food waste (FW) is a promising renewable low-cost biomass substrate for enhancing the economic feasibility of fermentative propionate production. Although lipids, a common component of food waste, can be used as a carbon source to enhance the production of volatile fatty acids (VFAs) during co-fermentation, few studies have evaluated the potential for directional propionate production from the co-fermentation of lipids and FW. In this study, co-fermentation experiments were conducted using different combinations of lipids and FW for VFA production. The contributions of lipids and FW to propionate production, hydrolysis of substrates, and microbial composition during co-fermentation were evaluated. The results revealed that lipids shifted the fermentation type of FW from butyric to propionic acid fermentation. Based on the estimated propionate production kinetic parameters, the maximum propionate productivity increased significantly with an increase in lipid content, reaching 6.23 g propionate/(L∙d) at a lipid content of 50%. Propionate-producing bacteria Prevotella, Veillonella, and norank_f_Propionibacteriaceae were enriched in the presence of lipids, and the succinate pathway was identified as a prominent fermentation route for propionate production. Moreover, the Kyoto Encyclopedia of Genes and Genomes functional annotation revealed that the expression of functional genes associated with amino acid metabolism was enhanced by the presence of lipids. Collectively, these findings will contribute to gaining a better understanding of targeted propionate production from FW.     

Economic simulation modeling of reprocessing alternatives for corn masa byproducts

Increasing production of corn masa for tortillas, chips, and related snack foods is resulting in large quantities of organic residuals requiring environmentally sound management. These byproduct streams appear suitable for use as livestock feed material, thus eliminating landfilling costs. Possibilities for developing livestock feed include direct shipping to livestock feeding facilities, blending prior to shipping, extrusion processing, pellet mill processing, and dehydration. To assess the viability of these options for reprocessing masa byproducts as livestock feed materials, an economic model was developed and applied to each of these alternatives. Through a series of simulation runs with this model, it was determined that direct shipping was by far the most inexpensive means of recycling masa processing residuals (10–57 $/Mg). Other alternatives examined in increasing order of costs included blending prior to shipping, extrusion, pellet mill processing (3–15, 5–18, and 4–18 times greater than direct shipping, respectively), while dehydration was clearly cost-prohibitive (33–81 times greater). Bagged feed was slightly more expensive to produce than bulk feed (1.1 times greater), and reprocessing costs increased as delivery distance increased, due to increased labor, equipment, and fuel costs, but decreased as byproduct generation rate increased, due to the development of the economies of scale. Alternately, based on a tipping fee of 50 $/Mg, the total estimated cost to landfill ranged from 65 to 112 $/Mg. Based on this cost analysis, direct shipping and feeding to livestock is the recycling option of choice for masa processing byproducts. Although specific details of process configurations and associated costs will vary, similar results are likely for other high moisture food processing residuals destined for utilization as livestock feed or components thereof.