Determination of specific gravity of municipal solid waste

This investigation was conducted to evaluate experimental determination of specific gravity (G_s) of municipal solid waste (MSW). Water pycnometry, typically used for testing soils was adapted for testing MSW using a large flask with 2000 mL capacity and specimens with 100–350 g masses. Tests were conducted on manufactured waste samples prepared using US waste constituent components; fresh wastes obtained prior and subsequent to compaction at an MSW landfill; and wastes obtained from various depths at the same landfill. Factors that influence specific gravity were investigated including waste particle size, compaction, and combined decomposition and stress history. The measured average specific gravities were 1.377 and 1.530 for as-prepared/uncompacted and compacted manufactured wastes, respectively; 1.072 and 1.258 for uncompacted and compacted fresh wastes, respectively; and 2.201 for old wastes. The average organic content and degree of decomposition were 77.2% and 0%, respectively for fresh wastes and 22.8% and 88.3%, respectively for old wastes. The G_s increased with decreasing particle size, compaction, and increasing waste age. For fresh wastes, reductions in particle size and compaction caused occluded intraparticle pores to be exposed and waste particles to be deformed resulting in increases in specific gravity. For old wastes, the high G_s resulted from loss of biodegradable components that have low G_s as well as potential access to previously occluded pores and deformation of particles due to both degradation processes and applied mechanical stresses. The G_s was correlated to the degree of decomposition with a linear relationship. Unlike soils, the G_s for MSW was not unique, but varied in a landfill environment due both to physical/mechanical processes and biochemical processes. Specific gravity testing is recommended to be conducted not only using representative waste composition, but also using representative compaction, stress, and degradation states.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

活性炭纤维负载TiO2催化剂的制备及其电催化性能

采用溶胶-凝胶法制备了活性炭纤维负载TiO₂催化剂（TiO₂/ACF）,并通过SEM和XRD等手段对TiO₂/ACF进行了表征。以邻苯二甲酸二甲酯（DMP）为目标降解物,考察了催化材料的电催化活性。实验结果表明：在反应温度为25 ℃、初始DMP质量浓度为100.0 mg/L、电解质Na₂SO₄质量浓度为100 mg/L、电流密度为62.5 mA/cm²、电极板间距为4 cm的条件下,经过40 min的降解,DMP质量浓度为1.8 mg/L,DMP去除率为98.2%;TiO₂/ACF在反应过程中可以原位再生,经6次重复使用后仍保持很高的催化活性,对DMP的去除率仍达90%以上。     

生物炭修复Cd,Pb污染土壤的研究进展

随着矿产开采、冶炼等工业活动以及污水灌溉、施用污泥和劣质化肥等农业活动的进行,Cd,Pb等有害重金属不断进入农业环境中,对农田、菜地等造成污染。生物炭作为重要的土壤改良剂,在对Cd,Pb污染土壤的修复中表现出巨大的潜力。从生物炭的特性及制备、修复效果及其影响因素、修复机理等方面,对近年来国内外有关生物炭修复Cd,Pb污染土壤的研究成果和现状进行了总结,并对生物炭修复Cd,Pb污染土壤的发展前景和未来研究方向进行了展望。     

分子筛催化剂生产废水的生物处理

采用氨化—硝化—反硝化三段联合生物工艺处理分子筛催化剂生产过程中产生的含有机胺废水。实验结果表明：在氨化过程中,当进水COD稳定为1 200~1 600 mg/L时,出水COD低于300 mg/L,COD去除率稳定在80%左右,当进水ρ（有机氮）为100~160 mg/L时,出水ρ（有机氮）均低于30 mg/L,有机氮去除率大于80%,在整个氨化过程中,出水ρ（氨氮）较进水ρ（氨氮）提高了35~200 mg/L;硝化过程中,当进水ρ（氨氮）小于等于300 mg/L时,出水ρ（氨氮）最终稳定在15 mg/L以内,氨氮去除率大于90%;在反硝化过程中,亚硝酸盐氮去除率基本稳定在98%以上,最终出水COD低于80 mg/L,出水ρ（总氮）低于25 mg/L。     

石化行业的VOCs排放控制管理

概述了我国挥发性有机化合物（VOCs）的排放情况。介绍了国内外VOCs的管理现状。分析了国内石化行业VOCs排放控制管理中存在的主要问题以及污染物排放过程的类别。提出了明确定义、制定相关标准、完善分类管理体系、研究最佳的可行性控制技术等加强VOCs排放控制管理的对策和建议。     

微波再生载苯酚活性炭过程中再生产物分析

研究了载氮气和无载气2种条件下,微波再生载苯酚活性炭过程中再生产物的成分和苯酚随再生过程的去向分布。结果表明,无载气时,微波功率越高,再生反应器内温度越高,吸附质的高温裂解反应越彻底,再生产物以挥发性气体为主,有机质种类很少;而当微波功率较低或载氮气再生时,反应器内温度相对较低,苯酚难以被彻底分解,再生产物中含多种复杂的链状或环状有机物。此外,载氮气时,经气提、挥发而去除的苯酚量约占总吸附量的一半,再生炭上无苯酚残留,活性炭吸附性能可完全恢复乃至优化;无载气时,经挥发而去除的苯酚量只有19.9%,其余大量苯酚则在微波作用下裂解或缩合为其他物质随尾气而去除,且再生炭上仍有少量苯酚未被解吸出来。因此,前者活性炭再生的效果优于后者。     

用于石油污染土壤降解的高效降解菌的筛选及其降解条件优化

经过富集、分离优选出高效石油降解菌L-1,根据形态观察和生理生化特征初步鉴定为琼氏不动杆菌;采用单因素花盆实验模拟微生物原位修复并对其降解条件进行优化。结果表明,将高效石油降解菌应用于修复石油污染土壤,适宜接种量、表面活性剂浓度、CNP比、翻耕频率分别为15%、0.1%、100∶10∶1和1 d 1次;在该降解条件下修复28 d,可达到16.80%的石油降解率,远远高于土著微生物6.92%的降解率。     

低温硝基苯降解菌选育及在土壤修复中的应用

从硝基苯污染地下水中筛选出一株以硝基苯为唯一碳源和氮源的低温、高效降解菌,命名为XJ菌;初步鉴定XJ菌为革兰氏阴性微小短杆细菌、恶臭假单胞菌属,降解硝基苯遵循部分还原降解途径;在10℃下培养96 h,XJ菌对硝基苯的降解去除率达到91.1%,其中约有67.1%的硝基氮素转变成了氨氮。在10℃下利用XJ菌修复硝基苯污染土壤,修复时间为96 h时,硝基苯去除率达到85.7%,XJ菌密度及微生物脱氢酶活性保持较高的水平。本研究可为低温下硝基苯污染土壤的生物修复提供参考。     

5种植物材料的水解释碳性能及反硝化效率

碳源在硝酸盐去除过程中起电子供体的作用,是生物反硝化反应的关键物质之一。为解决污水处理脱氮时碳源不足抑制反硝化反应造成脱氮效率低的问题,本研究选取风车草、甘蔗渣、芦竹、美人蕉和稻草秆5种植物材料作为反硝化碳源,探讨不同植物材料的水解释碳能力和释放规律;并进一步以其水解液作为外加碳源,探讨其对反硝化脱氮效率的影响。研究结果表明,植物材料水解释碳过程符合二级动力学反应规律,不同植物材料的释碳能力具有显著性差异,以甘蔗渣在固液比1∶80时COD释放当量最大,为45.45 mg/L;添加植物水解液可显著提高反硝化脱氮效率,以芦竹水解液脱氮效果最好,达到71.9%。此外,碳氮比是影响脱氮效率的重要因素之一,以碳氮比为9时反硝化脱氮效果最佳。