Quantification of polychlorinated biphenyl contamination using human placenta as biomarker from Punjab Province,Pakistan

Environmental Science and Pollution Research - The present study biomonitored the placental polychlorinated biphenyl (PCB) concentrations in women from Punjab Province, Pakistan, that provides the...     

Slow-release nitrogen fertilizers enhance growth,yield, NUE in wheat crop and reduce nitrogen losses under an arid environment

Environmental Science and Pollution Research - Higher demands of food led to higher nitrogen application to promote cropping intensification and produce more which may have negative effects on the...     

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.     

Screening of human health risk to infants associated with the polychlorinated biphenyl (PCB) levels in human milk from Punjab Province,Pakistan

This study assessed the polychlorinated biphenyl (PCB) levels in human milk and its associated health risk to infants from rural and urban settings of five districts of Punjab Province, Pakistan. The ∑₃₄PCB concentrations ranged from 30.9 to 68.3 ng g^?1 on lipid weight (l.w.) basis. The ∑₈DL-PCB concentrations were ranged from 0.29 to 1.35 ng g^?1 l.w., (mean 6.2 ± 8.7 ng g^?1 l.w.), with toxicity equivalent to polychlorinated dibenzodioxins (PCDDs) ranging from 8.58 × 10^?6 to 0.05 ng TEQ g^?1 l.w. The spatial trend of PCB levels in human milk revealed higher bioaccumulative levels for urban mothers as compared with rural counterparts. The estimated daily intake (EDI) values of DL-PCBs to infants through trans-mammary transfer were considerably higher than tolerable daily intake limits established by WHO (i.e., 1–4 pg TEQ kg^?1 bw) and other globally recognized organizations. Similarly, the hazard quotient values for TEQ ∑₈DL-PCBs (range 1.21 to 79.87) were far above the benchmark value of 1 at all the sampling sites, indicating the high levels of adverse health risks to infants in the region through breast milk consumption. The ∑₃₄PCB levels were found to be negatively correlated with mother’ age (r = ?0.31; p = 0.02), parity (r = ? 0.85; p = 0.001), and infant’ birth weight (r = ? 0.73; p = 0.01). The present study suggests undertaking comprehensive public health risk assessment studies and firm regulatory measures to safeguard human health risks.

     

Higher hydrogen production by photocatalytic water splitting using a hollow tubular graphitic carbon nitride-zinc telluride composite

Environmental Chemistry Letters - Energy demand and pollution due to urbanization and industrialization are calling for clean energies such as dihydrogen (H2) obtained by water splitting. For that,...