Effect of ozone injection on the long-term performance and microbial community structure of a VOCs biofilter

For biofilters treating waste gases containing volatile organic compounds(VOCs), biomass accumulation is a common problem which will induce bed clogging and significant decrease in VOCs removal efficiency during long-term operation. In this study, ozone injection was developed as a biomass control strategy, and its effects on the biofilter performance and the microbial community structure were investigated in long-term operation. Two biofilters,identified as BF1 and BF2, were operated continuously for 160 days treating gaseous toluene under the same conditions, except that 200 mg/m3 ozone was continuously injected into BF1 during days 45–160. During the operation period, ozone injection did not change the toluene removal efficiency, while the pressure drop of BF1 with ozone injection was significantly lowered compared with BF2. The wet biomass accumulation rate of BF1 was 11 g/m~3/hr, which was only46% of that in BF2. According to the carbon balance result, ozone injection also increased the toluene mineralization rate from 83% to 91%, which could be an important reason for the low biomass accumulation. The PMA-q PCR result indicated that ozone injection increased the microbial viability of the biofilm. The high-throughput sequencing result also revealed that the dominant phyla and genera were not changed significantly by ozone injection, but some ozonetolerant genera such as Rhodanobacter, Dokdonella and Rhodococcus were enhanced by ozone exposure. All the results verified that ozone injection is capable of sustaining the long-term performance of biofilters by lowering the biomass accumulation, increasing the microbial viability and changing the microbial community structure.     

澳大利亚碳交易体系下的经济援助系统

澳大利亚碳交易机制正式实施,配套的经济援助系统为其提供了合理、合法、全方位的保障措施,为企业转向清洁生产提供良好的过度环境。援助系统主要分为工业援助与居民援助两大部分,对澳大利亚碳交易机制的经济扰动进行了系统调节。这些援助系统的设计优点可为中国碳交易市场建设提供经验借鉴。     

基于粒子群算法的城市垃圾中转站的空间布局研究

随着城市化的进程，垃圾处理设施成为影响城市化质量的重要指标。依据人们实际所关注的垃圾处理设施的总成本和负效应两个因素，在前人研究的基础上，建立了垃圾收运多目标模型，使得总成本和负效应最优化。根据模型设计了粒子群算法，该算法属于智能算法，且精度高，收敛快，在许多领域也得到广泛应用。用设计的粒子群算法并结合案例求出了Pareto最优解，给出三种决策方案，验证了模型和算法的有效性和可行性，为决策者提供了一种理论参考。     

Process design for the environment: A multi-objective framework under uncertainty

Designing chemical processes for the environment requires consideration of several indexes of environmental impact including ozone depletion, global warming potentials, human and aquatic toxicity, photochemical oxidation, and acid rain potentials. Current methodologies, such as the generalized waste reduction algorithm (WAR), provide a first step towards evaluating these impacts. However, to address the issues of accuracy and the relative weights of these impact indexes, one must consider the problem of uncertainties. Environmental impacts must also be weighted and balanced against other concerns, such as their cost and long-term sustainability. These multiple, often conflicting, goals pose a challenging and complex optimization problem, requiring multi-objective optimization under uncertainty. This paper will address the problem of quantifying and analyzing the various objectives involved in process design for the environment. Towards this goal, we proposed a novel multi-objective optimization framework under uncertainty. This framework is based on new and efficient algorithms for multi-objective optimization and for uncertainty analysis. This approach finds a set of potentially optimal designs where trade-offs can be explicitly identified, unlike cost-benefit analysis, which deals with multiple objectives by identifying a single fundamental objective and then converting all the other objectives into this single currency. A benchmark process for hydrodealkylation (HDA) of toluene to produce benzene modeled in the ASPEN simulator is used to illustrate the usefulness of the approach in finding environmentally friendly and cost-effective designs under uncertainty.