Assessment of methane emission and oxidation at Air Hitam Landfill site cover soil in wet tropical climate

Methane (CH₄) emissions and oxidation were measured at the Air Hitam sanitary landfill in Malaysia and were modeled using the Intergovernmental Panel on Climate Change waste model to estimate the CH₄ generation rate constant, k. The emissions were measured at several locations using a fabricated static flux chamber. A combination of gas concentrations in soil profiles and surface CH₄ and carbon dioxide (CO₂) emissions at four monitoring locations were used to estimate the CH₄ oxidation capacity. The temporal variations in CH₄ and CO₂ emissions were also investigated in this study. Geospatial means using point kriging and inverse distance weight (IDW), as well as arithmetic and geometric means, were used to estimate total CH₄ emissions. The point kriging, IDW, and arithmetic means were almost identical and were two times higher than the geometric mean. The CH₄ emission geospatial means estimated using the kriging and IDW methods were 30.81 and 30.49 g m^?2 day^?1, respectively. The total CH₄ emissions from the studied area were 53.8 kg day^?1. The mean of the CH₄ oxidation capacity was 27.5 %. The estimated value of k is 0.138 year^?1. Special consideration must be given to the CH₄ oxidation in the wet tropical climate for enhancing CH₄ emission reduction.     

Geochemical assessment of metal concentrations in sediment core of Korangi Creek along Karachi Coast, Pakistan

Sediment core from Korangi Creek, one of the polluted coastal locations along the Karachi Coast Pakistan, was collected to trace the history of marine pollution and to determine the impact of industrial activity in the area. Down core variation of metals such as Ca, K, Mg, Al, S, Ti, V, Cr, Mn, Fe, Ni, Cu and Zn was studied in the 72.0 cm core. Nuclear analytical techniques, proton induced X-rays emission (PIXE), was employed to ascertain the chemical composition in sediment core. Grain size analysis and sediment composition of cored samples indicated that Korangi creek sediments are clayey in nature. Correlation matrix revealed a strong association of Ni, Cu, Cr and Zn with Fe and Mn. To infer anthropogenic input, enrichment factor (EF), degree of contamination and pollution load index were calculated. EF showed severe enrichment in surface sediment for Ni, Cu, Cr and Zn, indicating increased industrial effluents discharge in recent years. The study suggests that heavy metal discharge in the area should be regulated. If the present trend of enrichment is allowed to continue unabated, it is most likely that the local food web complexes in the creek might be at highest risk.     

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.     

Mercury contamination in the estuaries and coastal sediments of the Strait of Malacca

Fishers’ local ecological knowledge (LEK) is an additional tool to obtain information about cetaceans, regarding their local particularities, fishing interactions, and behavior. However, this knowledge could vary in depth of detail according to the level of interaction that fishers have with a specific species. This study investigated differences in small-scale fishers’ LEK regarding the estuarine dolphin (Sotalia guianensis) in three Brazilian northeast coastal communities where fishing is practiced in estuarine lagoons and/or coastal waters and where dolphin-watching tourism varies from incipient to important. The fishers (N?=?116) were asked about general characteristics of S. guianensis and their interactions with this dolphin during fishing activities. Compared to lagoon fishers, coastal fishers showed greater knowledge about the species but had more negative interactions with the dolphin during fishing activities. Coastal fishing not only offered the opportunity for fishers to observe a wider variety of the dolphin’s behavior, but also implied direct contact with the dolphins, as they are bycaught in coastal gillnets. Besides complementing information that could be used for the management of cetaceans, this study shows that the type of environment most used by fishers also affects the accuracy of the information they provide. When designing studies to gather information on species and/or populations with the support of fishers, special consideration should be given to local particularities such as gear and habitats used within the fishing community.     

Fuzzy Possibilistic Modeling for Closed Loop Recycling Collection Networks

Nowadays, in the competitive market, commercial companies due to their economic problems and also restrictions imposed by international organizations to comply with environmental regulations are making noticeable efforts to reduce the level of their wastes in their manufacturing systems and consequently the level of waste in consumers’ products. In harmony with this issue, one of the most effective ways which has successfully been used and proven to be economically profitable is to take products lifecycles into consideration. Consideration of products lifecycle has made supply chain practitioners to investigate the reverse logistics activities in addition to forward logistics activities. Hence, corporations, in order to reduce their cost on the one hand and boosting their efficiency on the other hand, were obligated to employ closed loop supply chain models to concurrently benefit from its economical and environmental advantages. Therefore, in this paper, a mixed nonlinear facility location–allocation model is proposed for recycling collection centers. The considered closed loop logistics model consists of multiple echelons, multiple suppliers, multiple collection centers, multiple time period and also multiple facilities. In real-life problems parameters like demand, cost, capacity, distances, and quantities of returned products are always uncertain. Therefore, in order to solve a realistic problem, foregoing parameters are considered as fuzzy in our proposed model. Subsequently, to solve fuzzy mixed nonlinear programming model, one of the most effective technique in the literature is used. Additionally, in order to demonstrate the behavior of the parameters employed in the model, a comprehensive sensitivity analysis is conducted. Computational results demonstrate that the proposed model can show favorable efficiency in solving supply chain problems.     

Visitor impact on rocky shore communities of Qeshm Island, the Persian Gulf, Iran

The influence of visitors on macroinvertebrates of rocky intertidal shores was investigated in southern coasts of the Qeshm Island, the Persian Gulf, Iran. Qeshm Island located at the Strait of Hormuz, with an area of 1,491 km², is the largest island in the region. This island consists of a number of important natural habitat types including creeks, mangroves, corals, and sandy, muddy, and rocky shores that accommodate diverse marine flora and fauna communities. Two rocky shores were selected at the touristic beaches being visited regularly, and further two control locations selected at pristine shores. Intertidal macroinvertebrates were collected from six microhabitats including rock platforms, cobbles, boulders, crevices, sea walls, and rock pools during two different periods representing high and low tourist seasons. Species richness, density, and assemblage structure in heavily visited shores were compared with that of control locations. Striped barnacles (Balanus amphitrite) were present on platforms of all locations, thus the changes in their size were used as the obvious contrast associated with visitor’s impact. A total of 70 macroinvertebrate species from 11 phyla were recorded. Significant differences were detected in taxonomic richness, density, and assemblage structure of macroinvertebrates between heavily visited and pristine shores, suggesting that macroinvertebrates were adversely affected by visitors’ impact at heavily visited shores. The test of changes in species richness, density, and assemblage structure from high to low seasons yielded mixed results. The significant changes in density and assemblage structure from high to low seasons were only observed in one heavily visited shore. A significant reduction in size of striped barnacles was observed only in one heavily visited shore. The opportunistic or fugitive species (e.g., small macroalgae and barnacles) were dominant macroinvertebrates on heavily visited shores indicating early succession stage. The results presented here showed that macroinvertebrates were adversely affected by human activities in subtropical rocky shore.     

Preconcentration of metal ions through chelation on a synthesized resin containing O, O donor atoms for quantitative analysis of environmental and biological samples

Nascent Amberlite XAD-4 has been used as the polymeric support for the synthesis of a stable extractor of metal ions, by incorporating phthalic acid through azo bridging. Elemental analyses and infra-red spectral and thermal studies were carried out for its characterization. The water regain value and hydrogen ion capacity were found to be 12.50 and 5.75 mmol g^?1, respectively. The optimum pH range for the maximum sorption of Ni(II), Mn(II), Cu(II), Zn(II), Cd(II), Cr(III), and Co(II) was observed at pH 5.5–8.0 with the corresponding half-loading time (t _1/2) of 9, 5, 9, 9, 3, 9, and 5 min, respectively. The preconcentration factor for Ni(II), Mn(II), Cu(II), Zn(II), Cd(II), Cr(III), and Co(II) are 190, 190, 190, 180, 180, 160, and 160, with the corresponding limit of preconcentration in the range of 5.25–6.25 μg L^?1. The detection limits, for flame atomic absorption spectrophotometry, were found to be 0.62, 0.60, 0.65, 0.75, 0.72, 0.84, and 0.85 μg L^?1, respectively. Method has been successfully applied to the analysis of water samples, multivitamin formulations, infant food substitutes, hydrogenated oil, and fishes.     

Performance of Cow Dung Reinforced Biodegradable Poly(Lactic Acid) Biocomposites for Structural Applications

In this work, performance of cow dung (CD) reinforced poly(lactic acid) (PLA) biocomposites was investigated for the potential use in load bearing application. CD of average 4 mm size was blended with PLA at different CD ratios (0–50 wt%) and their effects on the biocomposite properties were studied. The results showed an improvement in the flexural properties, while the tensile and impact strength dropped by 20 and 28% with the addition of 50% CD. The decline in the tensile and impact strength was due to micro-cracking and voids formation at higher CD content. Also, the incorporation of CD slightly decreased the thermal stability of the biocomposite. However, dynamic mechanical properties of the biocomposites generally improved. SEM analysis of tensile and impact fractured surfaces indicated that the CD had a reasonable adhesion with matrix. Moreover, the SEM micrographs of soil burial studies showed an accelerated degradation of higher CD wt% biocomposites.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.