废塑料再生过程废水中微塑料去除模拟试验

微塑料是一种存在于不同环境介质中的新兴污染物,主要来源于废弃塑料制品,其存在污染范围广、潜在环境污染大的问题.废塑料再生企业生产废水中微塑料浓度远高于其他类型废水,对其生产废水中的微塑料进行处理具有重要的环境意义.模拟废塑料再生过程的生产废水并进行微塑料去除的絮凝沉淀试验,研究絮凝剂投加量、pH、水力快速搅拌条件的单因素和正交试验对废水中微塑料去除率及其各因素作用的影响.结果表明:①当PAC (聚合氯化铝)投加量为10 mL,PAM (聚丙烯酰胺)投加量为7 mL,pH为9,水力快速搅拌条件为100 r/min下维持40 s再200 r/min下维持40 s时,微塑料的总去除率最高,达91%.②PAC投加量是影响微塑料去除效果的主要因素,其次是pH.③微塑料的去除率与其本身的密度有关,密度大的ABS (acrylonitrile butadiene styrene,丙烯腈-丁二烯-苯乙烯)去除率最高,密度小的PE (polyethylene,聚乙烯)去除率最低.④不同粒径区间的微塑料去除率区别较大,粒径小(0.1~0.25 mm)的微塑料去除效果最好.研究显示,通过控制PAC和PAM的投加量、pH和水力搅拌速率等条件,能够有效将废水中的微塑料通过絮凝沉淀的方法去除,从而达到净化含微塑料生产废水的目的.      

人工智能技术对长江流域水污染治理的思考

随着经济的快速发展和城市化进程的不断加速,促使水污染严重的长江流域需从污染物去除过程的建模与优化、污水处理过程的优化控制、水污染监测系统的构建开展水污染治理研究.传统的水污染处理技术存在污染物去除效率预测精度较低、污水优化控制成本较高、水污染监测滞后效应严重的问题.人工智能技术能够有效克服上述问题,因此通过梳理国内外学者利用人工智能技术在污水污染物去除过程的建模与优化、污水处理过程的优化控制及水污染监测系统的构建等方面的研究成果,为全面加强长江流域水污染治理能力提供科学可靠的技术指导.结果表明:①利用人工神经网络技术（径向基神经网络、多层前馈网络-人工神经网络、多层感知器神经网络）对污水污染物去除过程进行建模与优化,为精确预测长江流域重金属（Cr、Cu）、营养盐（TN、TP）、持久性有机污染物〔PBDEs（多溴二苯醚）、HCH（六氯环己烷）〕的去除率提供重要参考价值.②采用污水处理的自动控制技术与人工智能技术（递归神经网络、支持向量机、模糊神经网络等）构建污水智能控制系统,为长江流域实现高效节能的污水优化控制提供重要的技术指导.③利用在线监测仪器和人工智能技术（小波神经网络、多元线性回归-人工神经网络、叠层去噪自动编码器等）建立水污染智能监测系统,为解决长江流域水污染监测响应滞后问题提供有力的技术支持.因此,人工智能技术对长江流域提高污水污染物去除率,降低污水优化控制成本,提升水污染监测时效性具有重要的推广价值.      

CeO2形貌结构对催化湿式空气氧化苯酚性能的影响

采用水热法、沉淀法和溶胶凝胶法制备了3种不同形貌的CeO₂催化材料,并将其用于湿式空气氧化苯酚水溶液过程中,探讨了CeO₂形貌结构对催化湿式氧化苯酚水溶液性能的影响.采用扫描电子显微镜（SEM）、透射电子显微镜（TEM）、X射线衍射（XRD）、程序升温还原（TPR）等手段对CeO₂催化材料进行了表征.结果表明,水热法制备的CeO₂催化材料表现出较好催化性能,主要原因是水热法合成的CeO₂呈现交错的纳米棒状结构,主要暴露（220）晶面,且沿着（220）晶向生长.在反应温度为200℃、空气压力为2MPa、苯酚初始浓度500mg/L的条件下,最终（240min）COD的去除率为95.5%.     

Ni2+对好氧颗粒污泥系统性能的影响

以城镇污水处理厂A²/O工艺的回流污泥作为接种污泥,在序批式反应器（SBR）中培养好氧颗粒污泥（AGS）,探究Ni²⁺对AGS系统的影响.结果表明：在25℃的条件下,50d左右培养出成熟的AGS,其形态多呈球状或椭球状,外表分布着少量丝状菌,颗粒污泥粒径主要在2~4mm,MLSS达6000mg/L,SVI维持在40~50mL/g.将Ni²⁺作用于培养出的成熟AGS,Ni²⁺在0~2mg/L的浓度范围内会提高AGS的稳定性,使MLSS上升,SVI降低;同时会促进AGS分泌胞外多聚物（EPS）,EPS组成成分中的蛋白质（PN）明显多于多糖（PS）;Ni²⁺对好氧颗粒污泥去除总氮（TN）的抑制程度要大于COD,最终COD去除率可维持在95%以上,TN去除率可维持在70%以上.     

氮掺杂二氧化钛负载钒磷氧催化氧化NO的实验研究

以VPO为活性组分,N掺杂TiO 2为载体,采用浸渍法制备了VPO/TiN催化剂,基于单因素实验研究了其对NO的选择性催化氧化(SCO)性能以及抗硫抗水性能。研究表明:当P/V为1/5、N/Ti为1、活性组分负载量为10%、焙烧温度为350℃时,催化剂的SCO活性最好,NO氧化率达到61%;光致发光光谱(PL)表征显示N掺杂TiO 2在催化剂表面形成的氧空位可增强催化剂对O 2的吸附;VPO/TiN催化剂抗硫抗水性能较强,反应后的催化剂表面未发现硫酸根的特征峰,水蒸气主要通过与NO竞争吸附占据活性位点来抑制催化剂的SCO活性。     

基于铁锰泥的除砷吸附剂性能比较及吸附机理

为解决反冲洗铁锰泥粉末吸附剂（BSPA）使用后难以泥水分离问题,将除铁锰水厂生物滤池产生的反冲洗泥制成颗粒吸附剂（GA）和磁性粉末吸附剂（MPA）,并对BSPA、GA和MPA的除砷性能进行了比较,通过SEM、TED、XRD、BET、FTIR等技术对3种材料进行了表征,寻找3种吸附剂之间除砷性能差异的根源.结果表明,BSPA、GA和MPA对As （V）的最大吸附容量分别为40.980,5.048,8.694mg/g,改性后的吸附材料GA和MPA对砷的吸附能力下降.BSPA是一种以纤铁矿为主的无定形结构混合物,并混有针铁矿和结晶度差的水铁矿,GA的XRD图谱中出现石英晶体和少量赤铁矿晶体的衍射峰,而MPA的主要成分为结晶程度较高的磁赤铁矿.3种材料中均存在有利于吸附的含羟基官能团.BSPA、MPA和GA的比表面积分别为253.150,238.660,43.803m²/g.物相改变且结晶程度增加、表面羟基减少和比表面积降低是导致GA和MPA的砷吸附容量比BSPA低的主要因素.     

Pollution prevention at ports: clearing the air

Seaports are major hubs of economic activity and of environmental pollution in coastal urban areas. Due to increasing global trade, transport of goods through ports has been steadily increasing and will likely continue to increase in the future. Evaluating air pollution impacts of ports requires consideration of numerous sources, including marine vessels, trucks, locomotives, and off-road equipment used for moving cargo. The air quality impacts of ports are significant, with particularly large emissions of diesel exhaust, particulate matter, and nitrogen oxides. The health effects of these air pollutants to residents of local communities include asthma, other respiratory diseases, cardiovascular disease, lung cancer, and premature mortality. In children, there are links with asthma, bronchitis, missed school days, and emergency room visits. The significance of these environmental health impacts requires aggressive efforts to mitigate the problem. Approaches to mitigation encompass a range of possibilities from currently available, low-cost approaches, to more significant investments for cleaner air. Examples of the former include restrictions on truck idling and the use of low-sulfur diesel fuel; the latter includes shore-side power for docked ships, and alternative fuels. A precautionary approach to port-related air pollution would encourage local production of goods in order to reduce marine traffic, greener design for new terminals, and state-of-the art approaches to emissions-control that have been successfully demonstrated at ports throughout the world.     

太湖水质氮素质量浓度时空差异特征及影响因素分析

通过对2014—2016年湖体水质中氮素质量浓度分析,结合出入湖总氮浓度、水量、湖体水生生态等影响因素,发现太湖水体中总氮浓度呈现逐年下降的趋势,各监测点位总氮为0.530 mg/L～5.51 mg/L,时空分布不均,差异明显。时间上,总氮浓度表现为春季最高,夏季和秋季最低,且月均值变化曲线呈现出规律的正弦函数波形。空间上,总氮浓度大致表现出由西部湖区向东部湖区递减的趋势,呈现西部湖区﹥北部湖区﹥南部湖区﹥湖心区﹥东部湖区。要改善湖体水质,不仅要切断污染源,而且要加强水生生态功能修复。     

NBIAS中污泥龄对脱氮除磷效果的影响

探讨无回流间歇曝气系统 (简称 NBIAS) ,处理城市污水的污泥龄 ( SRT)对脱氮除磷及有机物去除效果的影响。通过原污水流程试验和人工合成污水静态模拟实验 ,试验结果表明 :在水温为 2 0℃～ 30℃ ,污泥负荷为 0 .2 5～0 .45kg CODcr/ kg MLSS· d,SRT为 1 8～ 2 2 d,HRT为 8～ 1 0 h时 ,利用原污水作为碳源 ,NBIAS在保持较高的 CODcr去除率的同时 ,总氮和总磷的去除率均在 80 %以上。     

Removal of high concentrated ammonia nitrogen from landfill leachate by landfilled waste layer

The landfill of municipal solid waste(MSW) could be regarded as denitrification reactor and involved in ammonia nitrogen biological removal process. In this research, the process was applied to municipal solid waste collected in Shanghai, China, which was characterized by high food waste content. The NH4^ removal efficiency in the system of SBR nitrifying reactor followed by fresh and matured landfilled waste layer in series was studied. In the nitrifying reactor, above 90% of NH4^ in leachate was oxidized to NO2^- and NO3^- . Then high concentrated NO2^- and NO3^- were removed in the way of denitrification process in fresh landfilled waste layer. At the same time, degradation of fresh landfilled waste was accelerated. Up to the day 120, 136.5 gC/(kg dry waste) and 17.9 gN/(kg dry waste) were converted from waste layer. It accounted for 50.15 % and 86.89 % of the total carbon and nitrogen content of preliminary fresh waste, which was 4.42 times and 5.17 times higher than that of reference column respectively. After filtering through matured landfilled waste, BOD5 concentration in leachate dropped to below 100 mg/L, which would not affect following nitrification adversely. Because the matured landfilled waste acted as a well methanogenic reactor, 23% of carbon produced accumulatively from fresh landfilled waste degradation was converted into CH4.