Regional prediction of long-term landfill gas to energy potential

Quantifying landfill gas to energy (LFGTE) potential as a source of renewable energy is difficult due to the challenges involved in modeling landfill gas (LFG) generation. In this paper a methodology is presented to estimate LFGTE potential on a regional scale over a 25-year timeframe with consideration of modeling uncertainties. The methodology was demonstrated for the US state of Florida, as a case study, and showed that Florida could increase the annual LFGTE production by more than threefold by 2035 through installation of LFGTE facilities at all landfills. The estimated electricity production potential from Florida LFG is equivalent to removing some 70 million vehicles from highways or replacing over 800 million barrels of oil consumption during the 2010-2035 timeframe. Diverting food waste could significantly reduce fugitive LFG emissions, while having minimal effect on the LFGTE potential; whereas, achieving high diversion goals through increased recycling will result in reduced uncollected LFG and significant loss of energy production potential which may be offset by energy savings from material recovery and reuse. Estimates showed that the power density for Florida LFGTE production could reach as high as 10 Wm(-2) with optimized landfill operation and energy production practices. The environmental benefits from increased lifetime LFG collection efficiencies magnify the value of LFGTE projects.     

Electro-Fenton pretreatment for the improvement of tylosin biodegradability

The feasibility of an electro-Fenton process to treat tylosin (TYL), a non-biodegradable antibiotic, was examined in a discontinuous electrochemical cell with divided cathodic and anodic compartments. Only 15 min electrolysis was needed for total tylosin degradation using a carbon felt cathode and a platinum anode; while 6 h electrolysis was needed to achieve high oxidation and mineralization yields, 96 and 88 % respectively. Biodegradability improvement was shown since BOD₅/COD increased from 0 initially to 0.6 after 6 h electrolysis (for 100 mg L^?1 initial TYL). With the aim of combining electro-Fenton with a biological treatment, an oxidation time in the range 2 to 4 h has been however considered. Results of AOS (average oxidation state) and COD/TOC suggested that the pretreatment could be stopped after 2 h rather than 4 h; while in the same time, the increase of biodegradability between 2 and 4 h suggested that this latter duration seemed more appropriate. In order to conclude, biological cultures have been therefore carried out for various electrolysis times. TYL solutions electrolyzed during 2 and 4 h were then treated with activated sludge during 25 days, showing 57 and 67 % total organic carbon (TOC) removal, respectively, namely 77 and 88 % overall TOC removal if both processes were considered. Activated sludge cultures appeared, therefore, in agreement with the assessment made from the analysis of physico-chemical parameters (AOS and COD/TOC), since the gain in terms of mineralization expected from increasing electrolysis duration appeared too low to balance the additional energy consumption.     

The effects of low frequency noise on mental performance and annoyance

Low frequency noise (LFN) as background noise in urban and work environments is emitted from many artificial sources such as road vehicles, aircraft, and air movement machinery including wind turbines, compressors, and ventilation or air conditioning units. In addition to objective effects, LFN could also cause noise annoyance and influence mental performance; however, there are no homogenous findings regarding this issue. The purpose of this research was to study the effects of LFN on mental performance and annoyance, as well as to consider the role of extraversion and neuroticism on the issue. This study was conducted on 90 students of Iran University of Medical Sciences (54 males and 36 females). The mean age of the students was 23.46 years (SD?=?1.97). Personality traits and noise annoyance were measured by using Eysenck Personality Inventory and a 12-scale self-reported questionnaire, respectively. Stroop and Cognitrone computerized tests measured mental performance of participants each exposed to 50 and 70 dBA of LFN and silence. LFNs were produced by Cool Edit Pro 2.1 software. There was no significant difference between mental performance parameters under 50 and 70 dBA of LFN, whereas there were significant differences between most mental performance parameters in quiet and under LFN (50 and 70 dBA). This research showed that LFN, compared to silence, increased the accuracy and the test performance speed (p?<?0.01). There was no association between LFN and noise annoyance (p?>?0.01). Introverts conducted the tests faster than extraverts (p?<?0.05). This research showed that neuroticism does not influence mental performance. It seems that LFN has increased arousal level of participants, and extraversion has a considerable impact on mental performance.     

Biomass and nutrient concentration of sweet corn roots and shoots under organic amendments application

Two field experiments were conducted at the Waimanalo research station on the island of O'ahu, Hawaii to study the effect of chicken (CM) and dairy (DM) manures on biomass and nutrient concentration in sweet corn roots and shoots. Sweet corn (super sweet 10, Zea Mays L. subsp. mays) was grown for two consecutive growing seasons under four rates of application (0, 168, 337, and 672 kg ha^{? 1} total N equivalent) and one time (OTA) or two time (TTA) applications of organic manure types and rates. There were significant effects of types, rates, and number of manure applications on dry biomass and macro- and micro-nutrient concentration in roots and shoots tissues. Results of root tissue indicated a significant accumulation of N and C under CM and DM treatments compared with the control treatment. Manure application rates significantly increased the accumulation of N and C in root tissue. Dry weight of roots and shoots and both macro- and micro-nutrient contents in the plant tissues significantly increased under TTA treatment compared with OTA treatment. There was a significant correlation (r² = 0.46 to 0.81) between root biomass, macro-, and micro-nutrient contents during both growing seasons. The results of the study indicates that amending soils with CM at the highest application rate provided the best crop performance in terms of root and shoot biomass, crop N, C, and other macro- and micro-nutrients.     

APPLICATION OF SELECTED SOIL LOSS EQUATIONS TO TRAMPLED SOIL CONDITIONS1

ABSTRACT: Soil loss prediction equations (Universal Soil Loss Equation, Modified Universal Soil Loss Equation, and Onstad-Foster Method) were modified to reflect the impact of trampling on soil erosion. The erosion control practice factor, P, was replaced by a trampling ratio, Tr, which is a function of the change in soil erosion due to animal trampling. Trampling impact on soil erosion varied With soil type. The data are a preliminary attempt to account for the impact of trampling on soil erosion.     

Solid phase extraction for evaluation of occupational exposure to Pb (II) using XAD-4 sorbent prior to atomic absorption spectroscopy.

Lead is an important constituent widely used in different industrial processes. For evaluation of workers' exposure to trace toxic metal of Pb (II), solid-phase extraction (SPE) was optimized. SPE using mini columns filled with XAD-4 resin was developed with regard to sample pH, ligand concentration, loading flow rate, elution solvent, sample volume, elution volume, the amount of resins, and sample matrix interferences. Lead ions were retained on a solid sorbent and then eluted, followed by a simple determination of analytes with flame atomic absorption spectrometery. The obtained recoveries of metal ions were greater than 92%. This method was validated with 3 different pools of spiked urine samples; it showed a good reproducibility over 6 consecutive days as well as 6 within-day experiments. This optimized method can be considered successful in simplifying sample preparation for a trace residue analysis of lead in different matrices when evaluating occupational and environmental exposures is required.     

Optimal redesign of groundwater quality monitoring networks: a case study

Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation–distance (T–D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T–D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T–D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.     

A mathematical model to predict the composition and generation of hospital wastes in Iran

The aim of this study is to investigate the quality and quantity of hospital wastes in Iran. The generated hospital wastes have been estimated by the number of hospitals and the number of active beds in each province of Iran in 2001. All data and information have been gathered from: (i) Iran Statistics Center, (ii) literature review, and (iii) hospital waste investigations for an average hospital. Physical analyses have been conducted in terms of various materials (plastic, textile, paper, metal, and others) and components (biological, infectious, medical, and regular wastes). Based on the above-mentioned investigation and information, a mathematical model has been developed to calculate the generation of (infectious) hospital wastes for any desired year. Utilizing the model, generated infectious hospital wastes has been estimated as 698,937 tones for 2008 (short-term) and 3,494,387 tones for 2028 (long-term period). If the real infectious wastes are collected separately, then the generated infectious wastes will be reduced by 15.1% of the above-mentioned amount (139,787 tones for 2008, and 698,877 tones for 2028). Results of physical analysis show the components of the hospital waste as: (a) infectious, 67.3%; (b) medical, 8.8%; (c) biological, 1.8%; and (d) common municipal wastes, 22.1%. An appropriate collection method requires training the staff at hospitals along with preparation of the required facilities. Of course, both of these requirements are cost intensive.     

A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

In this study, an algorithm combining a multi-objective genetic algorithm (GA)-based optimization model and a water quality simulation model is developed for determining a trade-off curve between objectives related to the allocated water quantity and quality. To reduce the run-time of the GA-based optimization model, the main problem is decomposed to long-term and annual optimization models. The reliability of water supply is considered to be the objective function in the long-term stochastic optimization model, but the objective functions of the annual models are related to both the allocated water quantity and quality. The operating policies obtained using this long-term model provide the time series of the optimum reservoir water storages at the beginning and the end of each water year. In the next step, these optimal reservoir storage values are considered as constraints for water storage in the annual reservoir operation optimization models. The epsilon-constraint method is then used to develop a trade-off curve between the reliability of water supply and the average allocated water quality. The Young conflict resolution theory, which incorporates the existing conflicts among decision-makers and stakeholders, is used for selecting the best solution on the trade-off curve. The monthly reservoir operating rules are then calculated using an Adaptive Neuro-Fuzzy Inference System, which is trained using the optimal operating policies. The proposed model is applied to the 15-Khordad Reservoir in the central part of Iran. The results show that this simplified procedure does not reduce the accuracy of the reservoir operating policies and it can effectively reduce the computational burden of the previously developed models.