Heavy metal exposure and behavioral assessment of vultures in a captive environment

Environmental Science and Pollution Research - Heavy metals are a heterogeneous group of metals that can cause detrimental biological disruptions in vultures. Heavy metals play a threatening role...     

Identification of rainfall homogenous regions in Saudi Arabia for experimenting and improving trend detection techniques

Environmental Science and Pollution Research - In Saudi Arabia, identifying homogenous zones based on rainfall patterns is critical for ensuring a predictable and stable water resource and...     

Financial development,international trade,and environmental degradation: a nonlinear threshold model based on panel smooth transition regression

Environmental Science and Pollution Research - Environmental degradation has severely affected the natural cycle of ecosystem. It’s high time now and humans should execute strategies...     

Nexus between green logistic operations and triple bottom line: evidence from infrastructure-led Chinese outward foreign direct investment in Belt and Road host countries

Environmental Science and Pollution Research - The Belt and Road initiative (BRI) mainly relies on the traditional and underdeveloped logistical trade routes including the terrestrial and oceanic...     

Pharmacological evaluation of crude methanolic extract of Kalanchoe pinnata leaves

Medicinal plants play a crucial role in maintaining human health. Kalanchoe pinnata has been used for treatment of different ailments like infections, rheumatism, and inflammation. Data showed that Kalancho pinnata methanolic extract (100 or 1000 μg/ml) significantly inhibited growth of shoots (hypocotyls) and roots (radicals) of rice compared to control after 3 or 7 days treatment. Further, the Kalancho pinnata methanolic extract (50–1000 μg/ml) exhibited antioxidant properties and scavenged free radicals in dose-dependent manner compared with a standard antioxidant (ascorbic acid). Kalancho pinnata methanolic extract also possesses antifungal property that inhibited approximately 76% and 51% growth of Aspergillus flavous and Aspergillus niger, respectively, using the extract at 200 μg/ml.     

Managing bioremediation of a creosote‐contaminated superfund site by optimizing moisture and temperature in a biopile

Soil moisture content and temperature in a contaminated soil biopile equipped with immobilized microbe bioreactors (IMBRs) were optimized during ex situ bioremediation at a creosote‐contaminated Superfund site. Efficiency of remediation during warm summer months without soil‐temperature and moisture optimization was compared with that of cold winter months when corrective measures were applied. Significant reduction (35 percent) in total polycyclic aromatic hydrocarbons (PAHs) was observed, compared to 3.97 percent without corrective measures (p < 0.05). Kinetic rates (KRs) for total PAH removal were significantly enhanced from 3.93 to 50.95 mg/kg/day. KRs for removal of high molecular mass four‐to‐six‐ring PAHs were also significantly enhanced from 70.29 mg/kg/day to 97.45 mg/kg/day ( p < 0.05). Bioremediation of two‐ and three‐ring PAHs increased significantly from 15 percent to 40 percent. Benzo[a]pyrene toxicity equivalent mass (BaP_equiv) was significantly reduced by 48 percent with KR of 0.47 mg/kg/day as compared to 22 percent with KR of 0.14 mg/kg/day (p < 0.05). Soil moisture content was enhanced from 15.7 percent to 41.4 percent. © 2007 Wiley Periodicals, Inc.     

Health risk of arsenic in the alluvial aquifers of Lahore and Raiwind,Punjab Province,Pakistan: an investigation for safer well water

Environmental pollution has generated release of high amounts of arsenic (As) which ultimately are detected in the water of Indus Basin Punjab, Pakistan. The area is characterized by a semiarid climate, and alluvial deposits. This investigation, an extension of previously reported As-affected area in Lahore and Kasur, aimed to (1) assess the extent of water contamination in this area and (2) determine possible safer sites for future water use. In a comparative study, total As contamination of underground water from individual dwellings and community water supply of some villages located at the boundary of the Sheikhopura and Lahore districts, Pakistan were measured to compare with previously published data of villages located at the boundary of the Lahore and Kasur districts. The results showed variable levels of As in shallow drinking water wells and average concentration exceeding WHO guidelines value. As levels ranged from below 5.2 to 80 µg/L and mean 45.5 µg/L. The As concentrations were higher than WHO limits but lower than previous studied area. In addition, high salinity was found to be a serious concern for deteriorating groundwater quality rendering it unsuitable for drinking. Groundwater is predominantly of the Na–HCO₃ type with slightly alkaline pH. High pH values and competition of As with HCO₃ may serve as an important process for mobilization of As in the shallow groundwater of the region. Continuous monitoring and expansion of monitoring systems are necessary to establish safer wells within As-contaminated areas.     

Production and growth of microalgae in urine and wastewater: A review

Environmental Chemistry Letters - Issues of climate change, energy demand, and natural resources depletion are calling for circular methods to produce value-added products such as biomass, biofuel,...     

Synthesis of magnetite-based nanocomposites for effective removal of brilliant green dye from wastewater

Environmental Science and Pollution Research - The present study aims at evaluating the batch scale potential of cotton shell powder (CSP), Moringa oleifera leaves (ML), and magnetite-assisted...     

Support vector machine based prediction of photovoltaic module and power station parameters

ABSTRACT

The uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. An accurate output power prediction of a PV system helps in better design and planning. The present study is carried out for the prediction of output power of PV generating station by using Support Vector Machines. Two cases are considered in the present study for prediction. Case-I deals with the prediction of PV module parameters such as V_oc, I_sh, R_s, R_sh, I_max, V_max, P_max, and case-II deals with the prediction of power generation parameters such as P_DC, P_AC, and system efficiency. Historical data of PV power station with an installed capacity of 10 MW and weather information are used as input to develop four different seasons-based SVM models for all parameters. The performance results of the models are presented in terms of Mean Relative Error (MRE) and Root Mean Square Error (RMSE). Additionally, the performance results obtained with polynomial and Radial Based Function kernel are also compared to show that which kernel has better prediction accuracy, and practicability. The result shows that the minimum average RMSE and MRE for case-I with Radial Based Function kernel are 0.034%, 0.055%, 0.002%, 1.726%, 0.044%, 0.047%, 2.342%, and 0.005%, 0.014%, 0.079%, 0.885%, 0.005%, 0.007%, 0.013%, and for case-II with poly kernel are 0.014%, 0.016%, 0.149% and 0.011%, 0.0175, 1.03%, respectively. The present study will be helpful to provide technical guidance to the prediction of the PV power System.