Evaluation of the gene expression changes in Nile tilapia (<Emphasis Type="Italic">Oreochromis niloticus</Emphasis>) as affected by the bio-removal of toxic textile dyes from aqueous solution in small-scale bioreactor

A laboratory-scale bioremediation unit was designed, built and tested for the bio-removal of several Direct textile dyes. Four experiments were carried out to assess the efficiency of the bioremediation unit using Aspergillus niger fungal strain. Three commonly used Direct dyes and textile dyes mixture (simulated effluent: Direct brown, Direct violet, Direct green) were tested in this study. The strain of A. niger was efficient in the removal of the three Direct dyes. The decolorization percentages of the dyes after 24 h of incubation were 56.2, 51.7, and 95.4% for Direct brown, Direct green, Direct violet dyes, respectively. The percentages increased up to 79.4, 86.4, and 96.7% after 72 h of incubation for the same dyes, respectively. The results also showed that the fungal strain reduced the chemical oxygen demand values of simulated dye effluents from 165 to 564 mg/l with most of the dyes. The assessment of bioremediation products on biomodel was conducted using a fresh water fish. The liver and brain of Nile tilapia were tested to evaluate the expression of genes coding for several proteins related to stress such as metallothioneins (MTs), cytochrome P450 (CYP450), and heat shock proteins (HSPs). To assess the alterations in the gene expression, ten animals from each group were killed after 4 weeks of treatment. The results revealed significant increases in the brain and hepatic mRNA levels of all stress protein genes MT, CYP450, Hsp70a, b, and Hsp47 in the fish groups treated with industrial Direct violet, green, and brown dye water. Exposure of tilapia to bioremediation products after treatment with A. niger fungi reduced the over-expression of the stress protein genes in the brain and liver tissues.     

An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.     

Exporting natural capital: the foreign eco-footprint on Costa Rica and implications for sustainability

As the world economy ‘globalizes’, trade has become a major mechanism by which much of the human population supports its needs. While trade in resource commodities (natural income) can increase the well-being of people in both exporting and importing countries, it can also lead to depletion of natural capital and the loss of ecosystems integrity. In recent years, various researchers have attempted to address this problem using a consumption-based perspective on ecological change. Their work shows that the loss of ecosystem integrity in almost any region of the world can be attributed to both local and international consumer demand. This paper illustrates the utility of modified eco-footprint analysis in assessing export-related ecological change in Costa Rica. We quantify ecological footprint of consumers around the world on the productive ecosystems of Costa Rica, document the changing character of this footprint and highlight some of the linkages between production for export in Costa Rica and ecological degradation. We then discuss the implications of the increasing trade-based entanglement of nations for ecosystems and global sustainability.     

Social and ecological facets of pest management in Honduran subsistence agriculture: implications for IPM extension and natural resource management

In subsistence farming systems of the developing world, adoption of resource-conserving practices such as integrated pest management (IPM) is often strikingly low. This has partially been ascribed to researchers’ limited understanding of how technologies develop at the interface of the systems’ social and ecological components. In Honduras (Central America), there exists concern about limited adoption and diffusion of IPM technologies in certain smallholder production systems. In this study, we determine social and ecological drivers of IPM adoption in subsistence maize production in the country’s hillside environment. Honduran small-scale maize production is typified by a key insect pest (the fall armyworm, Spodoptera frugiperda) being partly kept at bay through action of a diverse natural enemy complex, including ants, social wasps, carabid beetles, and spiders. Local agricultural landscapes, primarily shaped through shifting cultivation, provide key resources to maintain this natural enemy diversity. These local ecological conditions and related natural enemy abundance strongly influence farmers’ agroecological knowledge and pest management practices. In the meantime, farmer practices are also affected by local communication networks, which help validate and spread IPM concepts and technologies. Based on our findings, we advocate a holistic approach to improve IPM extension through mapping of agroecological opportunities, visualization of regional patterns in farmer knowledge, and associated priority setting. Local IPM capacity could be built through institutional strengthening and adaptive comanagement, while IPM training should be linked with natural resource management initiatives. These approaches may eventually improve the way IPM is delivered to small-scale farmers who operate in the ecologically diverse environments of the tropics.     

城市生活垃圾焚烧处理过程中重金属迁移规律研究

通过采集厦门2个垃圾焚烧发电厂进厂垃圾、渗滤液、飞灰、炉渣和烟气样品，分析垃圾组成成分及各组分的重金属含量，结果表明，垃圾中以厨余、橡塑类和纸类为主，共占到垃圾干基的78．08％，重金属含量大小次序为Zn〉Cu〉Pb〉Cr〉Ni〉Cd〉Hg；垃圾渗滤液中除Zn外，其他金属的含量都较低，一厂渗滤液中重金属Ni、Zn迁移量较大，分别达到24．46％和8．52％。二厂渗滤液中重金属的迁移有相同的趋势，但含量相对较高。垃圾焚烧后其重金属主要分布在飞灰和废渣中，烟气中的含量非常少，不同金属的含量均有差别，这与金属的性质有很大关系；通过浸出毒性分析，飞灰中重金属酸溶态含量多，容易浸出，属于危险废物。同时，不同烟气处理工艺产生的飞灰的重金属浸出量有很大差别。     

土壤Cd污染对跳虫Folsomia candida的生态毒性

采矿及冶炼等行为造成了严重的土壤重金属污染,其中Cd污染及其带来的健康风险近年来引起人们的高度重视。利用弹尾目跳虫开展土壤Cd污染的生态毒理研究,对Cd污染土壤的生态风险评价具有重要意义。本研究将跳虫Folsomia candida(F.candida)暴露在不同Cd浓度污染的人工土壤中,利用跳虫存活数量、繁殖数量及回避行为实验来评价重金属Cd污染对跳虫的生态毒性。结果表明,Cd对F.candida的急性毒性LC50值为2 086.93 mg·kg~(-1),慢性毒性的繁殖抑制(28 d)EC50值为224.95 mg·kg~(-1)。此外,Cd对跳虫回避行为影响的EC50(48 h)为721.26 mg·kg~(-1)。可以看出,慢性毒性的EC50值与Cd对回避行为影响的EC50值近似,但远低于急性毒性LC50值。因此,跳虫F.candida的回避行为和繁殖率对Cd污染土壤有较高的灵敏度,可用来表征土壤中Cd的生态毒性。     

Prediction of membrane fouling using artificial neural networks for wastewater treated by membrane bioreactor technologies: bottlenecks and possibilities

Membrane fouling is a major concern for the optimization of membrane bioreactor (MBR) technologies. Numerous studies have been led in the field of membrane fouling control in order to assess with precision the fouling mechanisms which affect membrane resistance to filtration, such as the wastewater characteristics, the mixed liquor constituents, or the operational conditions, for example. Worldwide applications of MBRs in wastewater treatment plants treating all kinds of influents require new methods to predict membrane fouling and thus optimize operating MBRs. That is why new models capable of simulating membrane fouling phenomenon were progressively developed, using mainly a mathematical or numerical approach. Faced with the limits of such models, artificial neural networks (ANNs) were progressively considered to predict membrane fouling in MBRs and showed great potential. This review summarizes fouling control methods used in MBRs and models built in order to predict membrane fouling. A critical study of the application of ANNs in the prediction of membrane fouling in MBRs was carried out with the aim of presenting the bottlenecks associated with this method and the possibilities for further investigation on the subject.     

Methane biofiltration in the presence of ethanol vapor under steady and transient state conditions: an experimental study

Methane (CH₄) removal in the presence of ethanol vapors was performed by a stone-based bed and a hybrid packing biofilter in parallel. In the absence of ethanol, a methane removal efficiency of 55 ± 1% was obtained for both biofilters under similar CH₄ inlet load (IL) of 13 ± 0.5 g_CH4 m^?3 h^?1 and an empty bed residence time (EBRT) of 6 min. The results proved the key role of the bottom section in both biofilters for simultaneous removal of CH₄ and ethanol. Ethanol vapor was completely eliminated in the bottom sections for an ethanol IL variation between 1 and 11 g_ethanol m^?3 h^?1. Ethanol absorption and accumulation in the biofilm phase as well as ethanol conversion to CO₂ contributed to ethanol removal efficiency of 100%. In the presence of ethanol vapor, CO₂ productions in the bottom section increased almost fourfold in both biofilters. The ethanol concentration in the leachate of the biofilter exceeding 2200 g_ethanol m^?3 _leachate in both biofilters demonstrated the excess accumulation of ethanol in the biofilm phase. The biofilters responded quickly to an ethanol shock load followed by a starvation with 20% decrease of their performance. The return to normal operations in both biofilters after the transient conditions took less than 5 days. Unlike the hybrid packing biofilter, excess pressure drop (up to 1.9 cmH₂O m^?1) was an important concern for the stone bed biofilter. The biomass accumulation in the bottom section of the stone bed biofilter contributed to 80% of the total pressure drop. However, the 14-day starvation reduced the pressure drop to 0.25 cmH₂O m^?1.     

Model and algorithm for bi-fuel vehicle routing problem to reduce GHG emissions

Because of the harmful effects of greenhouse gas (GHG) emitted by petroleum-based fuels, the adoption of alternative green fuels such as biodiesel and compressed natural gas (CNG) is an inevitable trend in the transportation sector. However, the transition to alternative fuel vehicle (AFV) fleets is not easy and, particularly at the beginning of the transition period, drivers may be forced to travel long distances to reach alternative fueling stations (AFSs). In this paper, the utilization of bi-fuel vehicles is proposed as an operational approach. We present a mathematical model to address vehicle routing problem (VRP) with bi-fuel vehicles and show that the utilization of bi-fuel vehicles can lead to a significant reduction in GHG emissions. Moreover, a simulated annealing algorithm is adopted to solve large instances of this problem. The performance of the proposed algorithm is evaluated on some random instances.