Institutional isomorphism and environmental sustainability: a new framework from the Shariah perspective

Environment, Development and Sustainability - Islam emphasizes the importance of environmental care, as prescribed in its primary sources of Shariah, the Quran and the authenticated actions and...     

Optimization of co-digestion of various industrial sludges for biogas production and sludge treatment: Methane production potential experiments and modeling

Optimal biogas production and sludge treatment were studied by co-digestion experiments and modeling using five different wastewater sludges generated from paper, chemical, petrochemical, automobile, and food processing industries situated in Ulsan Industrial Complex, Ulsan, South Korea. The biomethane production potential test was conducted in simplex-centroid mixture design, fitted to regression equation, and some optimal co-digestion scenarios were given by combined desirability function based multi-objective optimization technique for both methane yield and the quantity of sludge digested. The co-digestion model incorporating main and interaction effects among sludges were utilized to predict the maximum possible methane yield. The optimization routine for methane production with different industrial sludges in batches were repeated with the left-over sludge of earlier cycle, till all sludges have been completely treated. Among the possible scenarios, a maximum methane yield of 1161.53 m³ is anticipated in three batches followed by 1130.33 m³ and 1045.65 m³ in five and two batches, respectively. This study shows a scientific approach to find a practical solution to utilize diverse industrial sludges in both treatment and biogas production perspectives.     

Assessment of heavy metals in water,sediment, Anabas testudineus and Eichhornia crassipes in a former mining pond in Perak,Malaysia

The concentrations of Al, As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sn and Zn were analysed in water, sediment, muscle of climbing perch fish (Anabas testudineus), and tissue of water hyacinth plants (Eichhornia crassipes) collected from a former tin-mining pond in Perak, Malaysia. The monitoring was performed during the minimum and maximum rainfall periods. The concentrations of As, Cr, Fe, Ni, Pb and Zn in water exceeded the permissible limits set by the Interim National Water Quality Standards for Malaysia (INWQS). The risk index (RI) values determined for As, Cd, Cr, Cu, Hg, Pb and Zn in sediment presented a low degree of ecological risk. The order of the top three heavy metals measured in fish muscle was Zn?>?Fe?>?Al. The estimated daily intake (EDI) of As and Cr exceeded the allowable limits in both rainfall periods. The bioconcentration factor (BCF) and translocation factor (TF) values of Zn in water hyacinth were 24.865 and 3.214, respectively. The concentrations of Cu and Zn in the plant tissue were significantly correlated (p?<?.05) with the concentrations of heavy metals in water. Overall, climbing perch and water hyacinth are excellent bioindicators of environmental impacts on water bodies.     

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur

Long-term measurements (2004–2011) of PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) and trace gases (carbon monoxide [CO], ozone [O₃], nitrogen oxide [NO], oxides of nitrogen [NO_x], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], methane [CH₄], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM₁₀ concentration. In addition, this study includes source apportionment of PM₁₀ in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM₁₀ for 8 yr is 51.3 ± 25.8 μg m^?3, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM₁₀ on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM₁₀ identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and windblown particles (1%). However, the apportionment procedure left 28.0 μg m^?3, that is, 51% of PM₁₀ undetermined.

Implications: Air quality is always a top concern around the globe. Especially in the South Asian regions, measures are not yet sufficient; as revealed in our studies, the concentrations of particulate matters exceed the tolerable limits. Long-term data analysis and characterization of particular matters and their sources will aid the policy makers and the concerned authority to adapt measures and policies according to the circumstances. Additionally, similar intensive studies will give insight about future implications of air quality management.     

Inactivation of pathogenic micro-organisms in hospital waste using a microwave

The aim of this study was to investigate the efficiency of dry sterilization by microwave in the inactivation of pathogenic bacteria in blood wastes. Eight bacteria strains were selected for this purpose and these are S. aureus, Salmonella sp., E. faecalis, K. pneumonia, P. aeruginosa, E. coli, Streptococcus Group B and Bacillus sp. Sterilization by microwave was carried out at 385, 450 and 700 watts for 1, 5 and 10 min, respectively. Isolation and enumeration of pathogenic bacteria before and after treatments were carried out using direct plate technique and inactivation was determined in terms of log reduction. Increasing the running time and power to 10 min and 700 watts did not increase log reduction of most of pathogenic bacteria especially of gram negative bacteria. Revival of pathogenic bacteria during the storage period might be aided by the presence of a low moisture content which helps bacterial cells to revive but not to reproduce or over-grow. It can be concluded that dry sterilization of blood wastes by microwave reduces the number and limited re-growth of these pathogenic bacteria during storage time, due to the lower moisture content in the blood wastes.     

Nickel oxide nanoparticles exert cytotoxicity via oxidative stress and induce apoptotic response in human liver cells (HepG2)

Increasing use of nickel oxide nanoparticles (NiO NPs) necessitates an improved understanding of their potential impact on human health. Previously, toxic effects of NiO NPs have been investigated, mainly on airway cells. However, information on effect of NiO NPs on human liver cells is largely lacking. In this study, we investigated the reactive oxygen species (ROS) mediated cytotoxicity and induction of apoptotic response in human liver cells (HepG2) due to NiO NPs exposure. Prepared NiO NPs were crystalline and spherical shaped with an average diameter of 44 nm. NiO NPs induced cytotoxicity (cell death) and ROS generation in HepG2 cells in dose-dependent manner. Further, ROS scavenger vitamin C reduced cell death drastically caused by NiO NPs exposure indicating that oxidative stress plays an important role in NiO NPs toxicity. Micronuclei induction, chromatin condensation and DNA damage in HepG2 cells treated with NiO NPs suggest that NiO NPs induced cell death via apoptotic pathway. Quantitative real-time PCR analysis showed that following the exposure of HepG2 cells to NiO NPs, the expression level of mRNA of apoptotic genes (bax and caspase-3) were up-regulated whereas the expression level of anti-apoptotic gene bcl-2 was down-regulated. Moreover, activity of caspase-3 enzyme was also higher in NiO NPs treated cells. To the best of our knowledge this is the first report demonstrating that NiO NPs caused cytotoxicity via ROS and induced apoptosis in HepG2 cells, which is likely to be mediated through bax/bcl-2 pathway. This work warrants careful assessment of Ni NPs before their commercial and industrial applications.     

Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems

This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO₃, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH₃, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH₃, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.     

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

This article presents a two-stage maximum power point tracking (MPPT) controller using artificial neural network (ANN) for photovoltaic (PV) standalone system, under varying weather conditions of solar irradiation and module temperature. At the first-stage, the ANN algorithm locates the maximum power point (MPP) associated to solar irradiation and module temperature. Then, a simple controller at the second-step, by changing the duty cycle of a DC–DC boost converter, tracks the MPP. In this method, in addition to experimental data collection for training the ANN, a circuit is designed in MATLAB-Simulink to acquire data for whole ranges of weather condition. The whole system is simulated in Simulink. Simulation results show small transient response time, and low power oscillation in steady-state. Furthermore, dynamic response verifies that this method is very fast and precise at tracking the MPP under rapidly changing irradiation, and has very low power oscillation under slowly changing irradiation. Experimental results are provided to verify the simulation results as well.