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.     

Production of semiochemical and allelobiotic agents as a consequence of aphid feeding

Aphids have an extremely intimate relationship with their plant hosts. Although this might suggest that aphid infestation would be largely cryptic, there are a wide range of changes that can be detected behaviourally, chemically and also at the molecular genetic level. Colonisation by aphids can cause release of semiochemicals characteristic of the aphid species and besides reducing acceptability to incoming aphids; these can enable recruitment of specific parasitoids. Some semiochemicals involved in these processes can also influence the defence status of neighbouring intact plants through air or the rhizosphere. Electrophysiological and behavioural studies on the aphids, their parasitoids and other organisms facilitate the identification of compounds having direct effects on plant defence. New developments from work on semiochemicals such as (Z)-jasmone and 6-methyl-5-hepten-2-one, and allelobiotic agents such as 6-hydroxy-1,2,3,4-tetrahydro-β-carboline-3-carboxylic acid and 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one, as well as new work on these compounds and others as potential phytopheromones are discussed.     

Effects of long-term nitrogen addition and precipitation changes on CH4 flux in an alpine steppe北大核心CSCD

土壤是甲烷(CH4)重要的源和汇.氮沉降和降水格局变化正在急剧改变土壤碳循环,进而可能对土壤CH4通量造成深刻影响.高寒生态系统是巨大的碳库,对氮沉降和降水变化十分敏感.然而,目前多数研究集中在短期实验上,缺乏对长期氮沉降和降水变化背景下CH4通量的响应及其调控因素的认识.以青藏高原高寒草原为研究对象,在2013年搭建模拟氮沉降和降水格局改变实验平台.基于静态箱–气相色谱法测定2020年生长季(5-10月)土壤CH4通量.结果显示,高寒草原土壤呈CH4的汇.氮添加没有显著改变生长季和植物生长高峰CH4通量.然而,降水变化显著改变了生长季和植物生长高峰CH4通量,其中降水增加(+50%降水)降低了CH4的吸收(分别为–16%和–45%),降水减少(–50%降水)增强了CH4的吸收(分别为+73%和+33%).进一步研究发现,与植物属性和功能基因丰度相比,土壤环境因子主导了CH4通量变化(解释率>90%).其中CH4通量与土壤含水量和温度显著正相关,与土壤pH显著负相关.综上所述,在未来全球变化情景下,降水格局改变更能调节青藏高原高寒草原CH4通量的变化.(图6表1参37)     

Effects of pig manure compost and nonionic-surfactant Tween 80 on phenanthrene and pyrene removal from soil vegetated with Agropyron elongatum

This paper evaluates the effects of pig manure compost (PMC) and Tween 80 on the removal of phenanthrene (PHE) and pyrene (PYR) from soil cultivated with Agropyron elongatum. Soils spiked with about 300mgkg(-1) of PHE and PYR were individually amended with 0%, 2.5%, 5% and 7.5% (dry wt) of PMC or 0, 20 and 100mgkg(-1) of Tween 80. Unplanted and sterile microcosms were prepared as the controls. PAH concentration, total organic matter (TOM), dissolved organic carbon (DOC), total heterotrophic and PAH degrading microbial populations in soil were quantified before and after 60d period. The results indicated that A. elongatum could significantly enhance PYR removal (from 46% to 61%) but had less impact on PHE removal (from 96% to 97%). Plant uptake of the PAHs was insignificant. Biodegradation was the key mechanism of PAH removals (<3% losses in the sterile control). Increase in PMC or Tween 80 levels increased the removal of PYR but not of PHE. Maximal PYR removal of 79% and 92% were observed in vegetated soil receiving 100mgkg(-1) Tween 80 and 7.5% PMC, respectively. Enhanced PYR removal in soil receiving PMC could be explained by the elevated levels of DOC, TOM and microbial populations as suggested by Pearson correlation test. While the positive effect of Tween 80 on PYR removal could probably due to its capacities to enhance PYR bioavailability in soil. This paper suggests that the addition of either PMC or nonionic-surfactant Tween 80 could facilitate phytoremediation of PAH contaminated soil.     

An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

Effect of cadmium on nodulation and N2-fixation of soybean in contaminated soils

The effects of cadmium stress on nodulation, N2-fixation capabilities of the root nodule, the change in ultrastructure of the root nodule, soybean growth, and the distribution of cadmium in plants were studied. The results obtained show that the nodulation of soybean roots was greatly inhibited by the addition of Cd, especially at the addition level of 10 and 20 mg kg(-1) soil. The inhibition of plant growth, especially the root growth, increased as the cadmium concentration increased, with deleterious effects observed for the roots. The weight ratio of soybean root/leaf decreased as the Cd concentration increased, which might explain the reason for nodulation decreases. The results also indicate that N2-fixation of root nodule was stimulated to some extent at the low levels of Cd addition, but decreased sharply with further increase of the Cd concentration. High Cd levels were also associated with changes in the ultrastructure of root nodule, in which the effective N2-fixing area was reduced and the N2-fixing cells in the area also reduced. In addition, the results also reveal that the content of Cd in different parts of the plants was as follows: roots > stems > seeds, indicating that the accumulation of Cd by roots is much larger than that by any other part of the soybean plant, and might cause deleterious effects to root systems.     

Urban-Center CO Air Quality Projections

The distribution of mutagenic activity and nitroaromatic components of polycyclic organic matter (POM) in ambient air at industrial, urban, suburban, rural, and remote sites was studied using organic extracts from high volume aerosol samples. Direct-acting mutagens including 1-nitropyrene (1-NP), dinitropyrenes (DNP), and hydroxynitropyrenes (HNP) were measured by high performance liquid chromatography while the mutagenicity was determined in the Salmonella bioassay with strain TA-98. Benzo(a)pyrene (BaP), one of the possible precursors of nitroaromatic compounds in POM, was also measured. In comparing samples from a range of sites, TSP and the concentration of BaP per mass of particulate matter decreased, as expected, at greater distances from urban and industrial combustion sources. However, the concentrations of polar nitroaromatic POM compounds per mass of particles were higher at a remote site than in nonindustrial urban and suburban areas. The mutagenicity in particulate matter extracts from the remote area was predominantly (>90 percent) in the very polar fractions. There were also high atmospheric levels of nitroaromatic compounds and mutagenicity in heavily industrialized areas. These observations may reflect the influences of source emissions, atmospheric transformations of POM compounds, and ther atmospheric processes on the composition of ambient suspended particulate matter.