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。     

混合堆肥过程中挥发性固体含量的层次效应及动态变化

城市污泥与猪粪混合堆肥表明:升温期和高温期堆体上部有机物降解的差异较大,降温期堆体下部各层有机物降解的差异较大,且堆体内挥发性固体(VS)含量已形成明显的层次效应,腐熟期堆体中部有机物降解的差异较大,堆体内VS含量的层次效应仍很明显;不同堆肥期堆体内VS含量的差异由大到小分别为:降温期≥腐熟期>高温期>升温期,不同部位有机物降解程度由大到小为:上部>中部>下部;VS含量随时间的变化满足一级反应动力学方程,城市污泥和猪粪混合堆肥过程中VS的降解速率约为0.3kg·d^-1,VS含量降低了8.2%.     

生活垃圾堆肥分阶段反应动力学研究

根据堆肥不同阶段特点 ,通过接种和不接种堆肥实验 ,分别研究升温 -高温阶段和高温 -降温阶段动力学。从得到的动力学方程分析可知 :接种复合微生物菌剂 ,在升温 -高温阶段最大反应速率比对照组提高约 13 8.7 ;在高温 -降温阶段最大反应速率比对照组大 4.73 g/( h· kg) ,而半速系数 Km比对照组下降了 10 3 g/kg。说明接种复合微生物菌剂不仅使反应速率增大 ,而且使半速系数减小 ,使底物与酶反应更完全 ,有机物分解更迅速、更彻底     

连续流新型厌氧反应器处理固体有机废物研究

采用自行设计的连续流厌氧消化反应器,接种瘤胃微生物后,对纤维素进行连续降解,固体有机物质负荷可以达到14g/L·d。在此符合范围内,反应器内pH值、挥发酸产量及产气量都很稳定,不会对反应产生抑制作用。     

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.     

高效液相色谱-串联质谱法同时测定地表水中33种药物

采用固相萃取-高效液相色谱-串联质谱法(SPE-HPLC-MS/MS)建立了地表水中25种抗生素类药物和8种非抗生素类药物的分析方法。通过重点优化质谱参数、色谱条件、样品pH、洗脱溶剂组成及用量等确定了最佳分析条件。水样经过滤、固相萃取柱富集净化后,选择Shim-pack XR-ODS为色谱柱,以乙腈和0.2%甲酸-2 mmol/L乙酸铵-水溶液为流动相进行梯度洗脱,采用电喷雾电离源,在多反应监测模式下(MRM)分析测定,内标法定量。33种药物的仪器定量限为0.012～4.68 ng/L,方法检出限为0.011～7.60 ng/L,地表水加标回收率为53.7%～122%,相对标准偏差为1.22%～32.1%(n=6)。方法成功应用于北京市凉水河12个地表水样分析,共检出32种药物,检出质量浓度为未检出～239 ng/L。利托那韦(RTV)作为新型冠状病毒诊疗方案中推荐的药物在凉水河检出率为100%。     

Volatilization of heavy metals during incineration of municipal solid wastes

Incineration experiments with MSW, which had been impregnated with heavy metals, were presented to obtain information on the volatilization behavior of the elements cadmium (Cd), lead (Pb), and zinc (Zn) under different conditions. Experiments were carried out in a bubbling fluid bed system connected to a customized inductively coupled plasma optical emission spectroscopy(ICP-OES) for analyzing metals in the flue gas. The results indicated that the combustion temperature, the gas atmosphere, and the chlorine content in the flue gas could affect the volatilization behavior of heavy metals. In the fluidized bed combustion, a large surface area was provided by the bed sand particles, and they may act as absorbents for the gaseous ash-forming compound. Comparer with the metals Cd and Pb, the vaporization of Zn was low. The formation of stable compounds such as ZnO.Al2O3 could greatly decrease the metals volatilization. The presence of chlorine would enhance the volatilization of heavy metals by increasing the formation of metal chlorides. However, when the oxygen content was high, the chlorinating reaction was kinetically hindered, which heavy metals release would be delayed.     

Neutron activation analysis of ceramic tiles and its component and radon exhalation rate

IntroductionCeramic,consistofearthymaterialslikeclaykaolin ,limestoneandsandglass .Ceramicmaterialsarenonmetalic ,inorganiccompoundsprimaryoxides ,alsocarbides ,nitridesandsilicides .Twotypesofbondingmechanismsoccurinceramicmaterial ,ionicandcovalent.Theo…