Performance evaluation of sequencing batch reactor for beverage industrial wastewater treatment

Attempts were made in this study to examine the effectiveness of sequencing batch reactor (SBR) for the treatment of beverage industrial wastewater. The SBR was operated at three different organic loading rates (OLRs): 2, 1.7 and 1.1 kg COD/m3 d. Results of continuous long-term operation showed that by decreasing OLR from 2 to 1.7 kg COD/m3 day, the removal efficiency was increased from 95.5 to 99.3% for COD, from 95.3 to 98.1% for BOD and from 87 to 97.7% for TSS. While further decreasing of the OLR to 1.1 kg COD/m3 day, there is no significant adverse effect on organics removal. Also, residual total nitrogen (TN) concentration decreased by decreasing the OLR. However, increasing the OLRs exerted a slightly negative effect on the removal of total phosphorous. On the other hand, the experimental data indicated that the substrate utilization kinetic followed Monod's kinetics model approximately. The maximum specific substrate utilization rate (micro(max), half velocity coefficient (Ks), growth yield coefficient (Y) and decay coefficient (Kd) were 2.94 d(-1), 15.22 mg/L, 0.2384 g VSS/g COD and 0.2019 h(-1), respectively.     

Feedstock quality and growth of bioenergy crops fertilized with sewage sludge

Sewage sludge is rich in essential plant nutrients, but its use is restricted for crop production due to the pollutants it contains, such as metalloids and heavy metals. Sludge is also very sticky and compact. Therefore, the objectives of this work were to evaluate (1) the impact of various amounts of sludge on bioenergy crop productivity and quality and (2) the use of peat as an adjuvant to reduce the stickiness, density and nutrient richness of the sludge. Three different applications of sludge were examined, high, low (50% of high) and low mixed with an equal volume of peat. The sludge-peat mix increased significantly leaf area and biomass accumulation of maize and hemp. High sludge and sludge-peat mix applications increased significantly the leaf area and biomass accumulation as well as the net photosynthesis of oilseed rape. High sludge application resulted in the highest heavy metal and metalloid accumulation in maize and hemp. Sludge-peat mix resulted in the highest heavy metal and metalloid accumulation in oilseed rape. However, the sludge-peat mix application provided the best feedstock quality in all three crops, since chloride, silicon and sulfur concentrations and ash content in plant material were the lowest of the three sludge treatments.     

Effects of chitosan on oxidative stress and metallothioneins in aquatic worm Tubifex tubifex (Oligochaeta, Tubificidae)

Chitosan is a natural polymer which has the property to elicit the natural defenses mechanism in plant and which can be an interesting biopesticides. It is then necessary to investigate the potential toxicity of chitosan for aquatic animal health. Metallothioneins (MTs) are low molecular weight proteins, mainly implicated in metal ion detoxification. Increase in MTs contents had been considered as a specific biomarker of metal exposure. However recently it has been demonstrated that MTs participate in several cellular functions such as regulation of growth and anti-oxidative defenses. Therefore, the induction of MTs has been investigated in the aquatic worms Tubifex tubifex exposed to chitosan. MTs levels in exposed worm increased significantly (p > 0.05) after 2, 4, and 7 days of exposure to different concentrations of chitosan (maximum + 158.19 +/- 10.2% after 2 days of exposure to 125 mgl(-1) of chitosan). Several antioxidant parameters including glutathione (GSH), glutathione-S-transferase (GST), glutathione reductase (GR), and catalase (CAT) were quantified in T. tubifex after 2, 4, and 7 days of exposure to chitosan. Exposure to chitosan had a negative effect on T. tubifex growth (maximum effect -6.11 +/- 1.6% after 7 days with 125 mgl(-1)) demonstrating the toxic effect of the pesticide. This growth rate decrease was accompanied by a reduction in protein contents. The activity of catalase (CAT), glutathione-S-transferase (GST), and glutathione reductase (GR) increased in response to the chitosan demonstrating an oxidative stress in the worms.     

The effect of air pollution on drivers’ safety performance

Environmental Science and Pollution Research - Numerous studies have determined the adverse effects of air pollution on the health, welfare, and comfort of humans. More recently, the effects of air...     

Variations in breeding success and daily nest survival of Whiskered Tern (<Emphasis Type="Italic">Chlidonias hybrida</Emphasis>) at two Iranian colonies

Variations in breeding success of the Whiskered Terns (Chlidonias hybrida) were studied in two wetlands; Anzali (2005 and 2008) and Zarivar (2007–2008) in north and west Iran. Nesting success was modeled and compared using information-theoretic approach implemented in program Mark in order to assess effects of colony locations, years and nest initiation dates on the probability of daily nest survival. Clutch size did not vary between colonies and years. Breeding success varied between colonies (Zarivar > Anzali), and years only in Anzali (2005 > 2008). Overall daily nest survival was 0.977. (95% LCI 0.973, UCI 0.981), equivalent to a Mayfield nest survival of 0.317. (95% LCI 0.255, UCI 0.387). Egg-laying periods and colony site were important covariates affecting the daily survival rates (Σω _i = 0.86 and Σω _i = 0.83, respectively), while, the support for the effect of year was less (Σω _i = 0.41). We concluded that Lake Zarivar provides a more favorable nesting location for Whiskered Terns probably because of little changes in rainfall and water depth during the breeding seasons which influence breeding performance.     

Chemical composition and antimicrobial activities of the essential oil from the seeds of Enterolobium contortisiliquum (leguminosae)

Seeds of Enterolobium contortisiliquum were subjected to steam distillation to obtain a light yellow essential oil in a yield of 3 ml/kg of seeds. The major components of the oil were identified using gas chromatography/mass spectrometry (GC-MS) and were furfural, limonene, linalool, estragole, carvone, and apiole with carvone representing more than 50% of the total composition. Antimicrobial activities of the essential oil were determined against four species of gram positive bacteria (Bacillus subtilis, Bacillus cereus, Staphylococcus aureus, Micrococcus luteus) and two gram negative bacteria (Klebsiella pneumoniae, Serratia Marcescencs). The essential oil inhibited the growth of all tested bacteria but was most effective against the gram positive bacteria. Chemicals that are responsible for the antibacterial effect of the essential oil were determined using the bio-autography thin layer chromatography (TLC) technique. The active compounds responsible for the activity were found to be carvone and estragole.     

A charge model for household waste management services: a case study of Tehran municipality

In practice, it is difficult to implement Pay-As-You-Throw charge systems based on accurate estimates of waste generation. In many cities, this is made impossible, due to lack of technical and administrative infrastructure and cultural considerations, especially in developing countries. This paper presents an alternative two-component charge model that is the combination of cost-accounting technique of Waste Management Services (WMSs) and econometric functions of waste generation. Practical and computation steps considered by the model are presented as a proposal to reform the current system of waste charge in Tehran municipality. The presented model is simple to implement and resolves some of the disadvantages of the traditional methods of waste charge systems, including insufficient revenue to cover the cost of waste management and unfairness related to social inequality.     

Optimized forest degradation model (OFDM): an environmental decision support system for environmental impact assessment using an artificial neural network

The purpose of this article is Artificial Neural Network (ANN) modeling using ecological and associated factors with forest degradation to predict the degradation of ecosystem, thereby enabling us to assess the environmental impacts of forest projects as an Environmental Decision Support System (EDSS). Results of the Multi-Layer Feed-Forward Network (MLFN), trained for Optimized Forest Degradation Model (OFDM), indicate that the performance of OFDM is more than other degradation models. Changes in forest management activities with higher value in sensitivity analysis help forest managers to decrease OFDM entity and environment impacts. The system is an intelligent EDSS, which allows the decision-maker to model criteria in forest degradation in order to reach and employ the optimal allocation plan. Considering results, multi criteria decision analysis (MCDA) approaches based on ANN, is an encouraging and robust method for solving MCDA problems.