氧化铝载体下二氧化氯催化氧化处理印染废水

研究了二氧化氯化学氧化体系和二氧化氯催化氧化体系。实验结果表明:单用二氧化氯化学氧化处理COD为2700mg/L的活性艳红染料配制废水时,最佳反应pH值为10,氧化剂经济用量为800mgClO2/L废水,反应时间为30min,COD去除率可达63%左右,氧化指数(COD削减量∶ClO2投加量)=2.18。当二氧化氯与自制催化剂所组成的催化氧化体系用于对活性艳红染料配制废水的处理时,最佳反应pH值为10左右,氧化剂经济用量为1000mgClO2/L废水,反应时间为90min,COD去除率可达83.4%,氧化指数=2.25。结果表明,二氧化氯催化氧化法是一种新型高效的处理难降解废水的技术,有着广阔的应用前景。     

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.     

The responses of the hepatosomatic index (HSI), 7-ethoxyresorufin-O-deethylase (EROD) activity and glutathione-S-transferase (GST) activity in sea bass (Dicentrarchus labrax, Linnaeus 1758) caged at a polluted site: implications for their use in environmental risk assessment

The present study investigates the response of three hepatic biomarkers in adult sea bass (Dicentrarchus labrax, Linnaeus 1758) caged at a wastewater outlet of an oil refinery with fish caged at a pristine site used as controls. The biomarkers that were investigated were the hepatosomatic index (HSI), 7-ethoxyresorufin-O-deethylase (EROD) activity and glutathione-S-transferase (GST) activity. In addition, we have measured the levels of polycyclic aromatic hydrocarbons (PAHs) and selected heavy metals (lead, cadmium, mercury, copper and zinc) in sediment samples at the polluted site. Although the polluted site had high environmental levels of PAHs and heavy metals, there was no difference in hepatic EROD activity and HSI between fish caged at the polluted site and controls. On the other hand, GST activity was significantly lower in fish caged at the polluted site compared to controls. Our results point out that the studied biomarkers have limited use in environmental risk assessment studies, at least when caged adult sea bass is used as the sentinel species and complex toxicant mixtures are involved.     

臭氧激光雷达技术及应用研究进展

差分吸收臭氧激光雷达是完善光化学立体监测体系的重要技术,因其高时空分辨率的廓线探测优势而得以迅速发展,目前已被广泛应用于对流层臭氧浓度的遥感探测。阐述了臭氧激光雷达的原理,归纳总结了雷达系统及关键技术的国内外最新研究进展,梳理了臭氧激光雷达在环境领域的应用现状,并基于我国城市臭氧污染问题现状和管理需求,初步探索设计了臭氧激光雷达监测网络业务应用的整体框架。指出了臭氧激光雷达技术及应用中存在厂家众多但缺乏统一的技术规范和行业标准,数据质量及准确性有待提高,与标准分析方法产生数据的可比性较差等不足之处;提出了核心部件国产化,系统小型化、自动化及商用化,多平台以及与其他监测方式联用等发展趋势。     

中国高精度温室气体排放清单编制研究进展

高精度温室气体排放清单是摸清区域碳排放来源、识别时空演变特征的数据基础,也是政府部门科学制定“减污降碳”策略、实现“双碳”目标的科技支撑。通过调研国内外组织机构、科研团队在高精度排放清单方面的成果,从核算范围、核算方法、时空化方法、评估与校验4个方面介绍了我国温室气体排放清单编制方法的研究进展。针对我国高精度温室气体排放清单研究区域分散、方法与格式不统一的问题,提出我国清单编制要逐步统筹本地化、精细化和动态化的发展建议。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

大都市地下空间开拓与环境地质问题

城市地下空间是一种宝贵的资源，我国城市地下空间开发利用虽已取得较大的进展，然而由此所引发的环境地质问题仍然是令人担忧的。本文就大都市地下空间的开拓的作用及其引发的环境地质问题进行了深入的探讨，并提出了解决这些环境地质问题的相应途径。     

沸石悬浮填料生物移动床的亚硝化特性

本研究以沸石为重要原料研制新型沸石悬浮填料,并将其用于启动沸石悬浮填料移动床反应器(ZMBBR),与装填普通陶粒的陶粒悬浮填料移动床(CMBBR)对比考察其亚硝化性能.结果表明:通过游离氨(FA)抑制的方法快速实现两种反应器的稳定亚硝化,两个反应器出水亚硝酸氮积累率均能达到90％以上;沸石对铵离子的吸附解吸作用使ZMB...     

基于“人工智能”驱动的农村生活污水系统治理专栏序言

伴随流域水污染控制与治理工作的深入,农村分散生活污水治理逐渐成为制约流域水环境改善的关键.同时,农村生活污水治理是人居环境提升、美丽乡村建设以及乡村振兴战略实施的集中体现,事关广大农村居民的切身利益.本专栏是国家水专项“分散污水治理课题”团队近年来科研成果的总结,从污水治理的全生命周期角度出发,尝试通过人工智能赋能治理模式决策、“菜单式”工艺组合、设施运维与监管、长效管理等4个方面对研究和实践进行了梳理总结,构建基于人工智能驱动的农村生活污水治理决策支持系统,以期为北运河流域以及其他区域农村生活污水治理提供科技支撑.