GIS-based statistical model for the prediction of flood hazard susceptibility

At present, flood is the most significant environmental problem in the entire world. In this work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of Bengal basin, India. Fourteen flood causative factors extracted from different datasets like DEM, satellite images, geology, soil and rainfall data have been considered to predict FS. Three heuristic models and one statistical model fuzzy Logic (FL), frequency ratio (FR), multi-criteria decision analysis (MCDA) and logistic regression (LR) have been used. The validating datasets are used to validate these models. The result shows that 68.71%, 68.7%, 60.56% and 48.51% area of the basin is under the moderate to very high FS by the MCDA, FR, FL and LR, respectively. The ROC curve with AUC analysis has shown that the accuracy level of the LR model (AUC?=?0.916) is very much successful to predict the flood. The rest of the models like FL, MCDA and FR (AUC?=?0.893, 0.857 and 0.835, respectively) have lesser accuracy than the LR model. The elevation was the most dominating factor with coefficient value of 19.078 in preparation of the FS according to the LR model. The outcome of this study can be implemented by local and state authority to minimize the flood hazard.

     

Distinct effects of intrinsic motivation and extrinsic rewards on radical and incremental creativity: The moderating role of goal orientations

Previous studies have investigated the role of intrinsic motivation and extrinsic rewards in enhancing employee creativity. However, the possibility that these motivational factors affect the creativity of different types remains largely unexplored, particularly in the organizational settings. Moreover, the potential that personality traits may moderate the function of these motivational factors toward creativity is another underresearched area. By drawing on the person–situation interaction perspective, we propose that both intrinsic motivation and extrinsic rewards predict creativity but of different types. Thus, we diverge from the view that creativity is a uniform criterion domain by adopting the distinction between radical and incremental creativity. Our empirical analysis of 220 independent employee–supervisor dyads confirmed that intrinsic motivation and extrinsic rewards predict radical and incremental creativity, respectively. Moreover, the effects of intrinsic motivation on radical and incremental creativity are more positive for employees with higher learning goal orientation. By contrast, the effect of extrinsic rewards on incremental creativity is more positive for employees with higher performance goal orientation. This study offers elaborate and nuanced perspectives and insights into the role of different motivational processes in the development of different types of creativity.     

Removal of heavy metal ions from aqueous system by ion-exchange and biosorption methods

Environmental Chemistry Letters - Pollution due to heavy metals is currently a serious problems affecting water bodies. The removal of heavy metals is of great concern due to their toxicity at...     

Correction to: Monitoring of copper accumulation in water,soil, forage,and cows impacted by heavy automobiles

Environmental Science and Pollution Research - A Correction to this paper has been published: https://doi.org/10.1007/s11356-021-13137-9     

Silver Nanoparticle Incorporated Flaxseed Protein-Alginate Composite Films: Effect on Physicochemical,Mechanical, and Thermal Properties

Journal of Polymers and the Environment - In the present study, flaxseed protein-alginate films were prepared with different concentrations of silver nanoparticles (AgNPs) and were evaluated for...     

Correlation of MSH2 exonic deletions and protein downregulation with breast cancer biomarkers and outcome in Pakistani women/patients

Environmental Science and Pollution Research - Mismatch repair (MMR) pathway is one of the underlying mechanisms of predisposition to breast cancer (BC). The present study explored the association...     

Fungal dye decolourization: recent advances and future potential

Dyes released by the textile industries pose a threat to the environmental safety. Recently, dye decolourization through biological means has gained momentum as these are cheap and can be applied to wide range of dyes. This review paper focuses on the decolourization of dye wastewaters through fungi via two processes (biosorption and bioaccumulation) and discusses the effect of various process parameters like pH, temperature, dye concentration etc. on the dye removing efficiency of different fungi. Various enzymes involved in the degradation of the dyes and the metabolites thus formed have been compiled. Genetic manipulations of microorganisms for production of more efficient biological agents, various bioreactor configurations and the application of purified enzymes for decolourization, which constitute some of the recent advances in this field, have also been reviewed. The studies discussed in this paper indicate fungal decolourization has a great potential to be developed further as a decentralized wastewater treatment technology for small textile or dyeing units. However, further research work is required to study the toxicity of the metabolites of dye degradation and the possible fate of the utilized biomass in order to ensure the development of an eco-friendly technology.     

Recent progress in bioethanol production from lignocellulosic materials: A review

Natural energy sources like petrol and diesel are going to be diminished in the coming future which will lead to increase in the prices and demands of fossil fuels. Therefore, it is important to find a sustainable alternate of fossil fuels. Bioethanol is one of the alternatives, which is produced from different feedstocks including sugar-based, starch-based and lignocellulose-based materials through fermentation. Since sugar-based (sugar cane and sugar beet) and starch-based (corn) materials are sources of staple food, therefore, research on lignocellulosic materials for bioethanol production is a subject of recent studies. Ethanol production from lignocellulosic materials involves different steps, such as pretreatment, hydrolysis, followed by fermentation process and finally ethanol purification. In this review, we have summarized the recent progresses in bioethanol production and processing from lignocellulosic materials.     

A contemporary landscape of air pollution and greenhouse gas emissions leads to inevitable phenomena of low birthweight

The objective of the study is to empirically examine the air pollution, greenhouse gas (GHG) emissions and low birth weight in Pakistan through the cointegration and error correction model over a 36-year time period, i.e., between 1975 and 2012. The study employed the Johansen cointegration technique to estimate the long-run relationship between the variables, while an error correction model was used to determine the short-run dynamics of the system. The study was limited to the following variables, including carbon dioxide emissions, methane emissions, nitrous oxide emissions, GHG emissions, and low birth weight in order to manage robust data analysis. The results reveal that air pollution and GHG emissions significantly affects the low birth weight in Pakistan. In the long run, carbon dioxide emissions act as a strong contributor for low birth weight, as the coefficient value indicates there is a more elastic relationship (i.e., ?1.214, p?p?p?相似文献   

Receptor modeling for source apportionment of polycyclic aromatic hydrocarbons in urban atmosphere

This study reports source apportionment of polycyclic aromatic hydrocarbons (PAHs) in particulate depositions on vegetation foliages near highway in the urban environment of Lucknow city (India) using the principal components analysis/absolute principal components scores (PCA/APCS) receptor modeling approach. The multivariate method enables identification of major PAHs sources along with their quantitative contributions with respect to individual PAH. The PCA identified three major sources of PAHs viz. combustion, vehicular emissions, and diesel based activities. The PCA/APCS receptor modeling approach revealed that the combustion sources (natural gas, wood, coal/coke, biomass) contributed 19–97% of various PAHs, vehicular emissions 0–70%, diesel based sources 0–81% and other miscellaneous sources 0–20% of different PAHs. The contributions of major pyrolytic and petrogenic sources to the total PAHs were 56 and 42%, respectively. Further, the combustion related sources contribute major fraction of the carcinogenic PAHs in the study area. High correlation coefficient (R ² > 0.75 for most PAHs) between the measured and predicted concentrations of PAHs suggests for the applicability of the PCA/APCS receptor modeling approach for estimation of source contribution to the PAHs in particulates.