Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

Infrastructure development through PPPs in India: criteria for sustainability assessment

Public private partnerships (PPPs) allow the Indian Government to leverage private capital for meeting the widening demand-supply gap in the provision of infrastructure services. The private sector, however, prefers to limit the participation to financially attractive projects only, thereby resulting in patterns of infrastructure creation impeding the progress towards sustainable development. In order to promote sustainable development, the PPP procurement process should focus on incentivising the private sector for sustainable infrastructure development rather than concentrating on ensuring financial sustainability only. This paper discusses the principles-based PPP-specific framework that has been developed to facilitate assessment of PPP projects' progress towards sustainable development. The framework development was based on a holistic approach to sustainability assessment and subsequently validated through questionnaire survey with key stakeholders in the Indian PPP programme. This framework will provide the decision makers with appropriate decision aid for integration of sustainable development principles in the PPP procurement process.     

Application of environmental risk assessment for strategic decision-making in coastal areas: case studies in China

Environmental risk assessment (ERA) is a powerful technical tool for analyzing potential and extreme adverse environmental impacts, and has found wide application in supporting decision-making processes over the last two decades. However, to date there has been no interrelated application of ERA to support the processes of strategic decision-making (SDM), especially in coastal areas.

In this paper, we attempt to verify the feasibility of the proposed integrated ERA–SDM approach and its methodology by applying it to two case studies (in Xiamen Bay and Luoyuan Bay) of the principal coastal functional zoning (PCFZ, a kind of SDM and similar to the coastal and marine spatial planning in western). The results show that the integrated ERA–SDM approach could integrate ERA into the entire SDM process, directly support the PCFZ, and avoid or mitigate dire environmental risk that can be introduced by SDM processes.     

固体废物全过程管理中固体废物鉴别研究

对固体废物应进行全过程管理,固体废物鉴别是固体废物全过程管理的基础和关键,包括依据产生来源鉴别和过程鉴别两种方法,依据产生来源鉴别包括丧失原有利用价值的物质、在生产过程中产生的副产物、环境治理和污染控制过程中产生的物质、其他物质四类,在每一类中详细地列举了属于该产生来源的具体固体废物种类名称,便于理解和增强可操作性。过程鉴别包括在固体废物再生利用过程和处置过程中的固体废物鉴别两类,其中在再生利用过程的固体废物鉴别中明确指出了固体废物再生利用产物只有同时满足产品质量标准要求、国家污染控制标准要求以及有实际市场需求、固定用户等条件时,才不作为固体废物管理,在处置过程的固体废物鉴别中具体地列出了处置固体废物全过程中仍然作为固体废物管理的国际惯用处置方式。同时,给出了清晰的"原料—产品—固体废物—处置或产品"全过程中固体废物的产生节点和相应的固体废物类别图,为固体废物鉴别工作提供参考,使固体废物全过程管理有的放矢,有效防止固体废物对环境和人体健康造成的危害。     

Whole effluent toxicity assessment at a wastewater treatment plant upgraded with a full-scale post-ozonation using aquatic key species

Ozonation as final wastewater (WW) polishing step, following conventional activated sludge treatment is increasingly implemented in sewage treatment for contaminant degradation to prevent surface water pollution. While the oxidative degradation of chemicals has been extensively investigated, the in vivo toxicological characteristics of ozonated whole effluents are rarely a matter of research.In the present study, whole effluents were toxicologically evaluated with an in vivo test battery before and after full-scale ozonation and subsequent sand filtration on site at a treatment plant. One aquatic plant (duckweed, Lemna minor) and five invertebrate species of different systematic groups (Lumbriculus variegatus, Chironomus riparius, Potamopyrgus antipodarum, Daphnia magna) were exposed to the effluents in a flow-through-designed test system with a test duration of 7-28 d.None of the considered toxicity endpoints correlated with the pollutant elimination. A tendency towards an increased toxicity after ozonation was apparent in three of the test systems showing [statistically] significant adverse effects in the L. variegatus toxicity test (decrease in reproduction and biomass). After sand filtration, adverse effects were reduced to a similar level like after conventional treatment. Solely the Daphnia reproduction test revealed beneficial effects after ozonation in combination with sand filtration.Results of the test battery indicate the formation of adverse oxidation products during WW ozonation. L. variegatus appeared to be the most sensitive of the five test species. Sand filtration effectively removes or detoxifies toxic oxidation products, as toxic effects were subsequently reduced to the level after conventional treatment.     

实时荧光定量PCR对A2/O短程硝化系统内氨氧化菌的定量分析

通过控制好氧区低DO浓度以及缩短好氧实际水力停留时间(actual hydraulic retention time,AHRT),在处理低C/N比实际生活污水的A2/O工艺中,成功启动并维持了短程硝化反硝化;系统亚硝酸盐积累率稳定维持在90%左右,氨氮去除率在95%以上。通过提取富集氨氧化菌(ammonia oxidizing bacteria,AOB)的基因组DNA,经两次常规PCR扩增和琼脂糖凝胶电泳,以纯化回收的DNA扩增片段作为实时荧光定量PCR检测AOB数量的DNA标准品,建立了检测AOB数量的实时荧光定量PCR标准曲线。利用实时荧光定量PCR技术比较了A2/O系统在不同运行条件及亚硝酸盐积累率情况下AOB菌群数量。结果表明,随着系统亚硝酸盐积累率的上升,系统内AOB菌群数量也大幅上升。全程硝化和短程硝化时,系统内的AOB菌群数量分别为5.28×109cells/g MLVSS和3.95×1010cells/g MLVSS。此外,亚硝酸盐积累率的下降相对于AOB菌群数量的下降有一定的滞后性。     

太阳光Fenton法处理垃圾渗滤液中有机污染物

研究利用太阳光Fenton法处理垃圾渗滤液。根据太阳光辐射强度随时间的变化规律,选择重庆7、8月份的晴天,在中午12：00到下午14：00时进行试验,研究太阳光辐射时间、pH值、Fenton试剂用量对垃圾渗滤液COD去除率的影响。研究结果表明：太阳光Fenton法对垃圾渗滤液的COD有较好的去除效果,COD去除率达86.2%。太阳光Fenton法处理垃圾渗滤液的优化条件是：日光辐射时间为120 min,pH值为2.5,Fe²⁺浓度为5 mmol/L,H₂O₂浓度为570 mmol/L。同时,论文还对太阳光Fenton法处理垃圾渗滤液的动力学进行分析。研究结果显示：太阳光Fenton法处理垃圾渗滤液,其表观动力学方程为-dC/dt=2.6×10^-8×P^1.92×F^1.79×E^1.67。     

无锡太湖新城污水处理厂改良型A^2／O工艺的调试与运行

介绍了无锡市太湖新城污水处理厂的一期工程设计概况和所采用的改良型A^2/O脱氮除磷工艺，分析、探讨了污水处理厂的调试、培菌、试运行过程中出现的问题，并针对性地采用了一系列的解决措施。由监测数据表明，该工艺运行可靠，出水水质稳定，实现了污水处理厂的正常运行。     

厌氧-好氧工艺处理制药废水的中试研究

将由厌氧折流板反应器(ABR)、移动床生物膜反应器(MBBR)和膜生物反应器(MBR)组合而成的厌氧-好氧工艺用于处理制药废水的中试研究.试验结果表明,当原水SS平均值为1000 mg/L,COD为10 000 mg/L,NH3-N为500 mg/L时,出水浊度、COD和NH3-N分别为3 NTU、500 mg/L以及10 mg/L以下,去除率分别为98%、95%和98%以上.     

响应面法优化超临界水氧化处理农药废水

在间歇式超临界水氧化系统中对草甘膦农药废水进行降解实验。选取温度、反应时间、过氧量3个量为因素量,总有机碳(TOC)去除率为响应量进行中心组合设计（CCD）。在实验的基础上,利用响应面分析法（RSM）对实验结果进行分析及参数优化：建立了TOC去除率与各个因素关系的二次多项式数学模型;分析了各个因素单独的及相互作用对TOC去除率的影响;优化结果表明,在温度483℃、反应时间29.2 min、过氧量148.4%的条件下,达到了最佳效果,此时TOC的去除率为100%。