Adoption of green banking practices and environmental performance in Pakistan: a demonstration of structural equation modelling

Environment, Development and Sustainability - Banking industries are blamed to be among the major factors that affect global climate change both directly and indirectly. The green banking concept...     

Forecasting the impact of meteorological parameters on air pollutants in Andhra Pradesh using machine learning techniques

In the 21st century, air pollution has emerged as a significant problem all over the globe due to a variety of activities carried out by humans, such as the acceleration of industrialization and urbanization. SO₂, NO₂, and NH₃ are the key components contributing to air pollution. Moreover, these air pollutants have a significant connection to several climatic characteristics, such as the speed of the wind, the relative humidity, the temperature, the amount of precipitation, and the surface pressure. As a result, machine learning (ML) is regarded as a more effective strategy for predicting air quality than more conventional approaches such as probability and statistics, among others. In the research, Decision Tree (DT), Support Vector Regression (SVR), Random Forest (RF), and Multi-Linear Regression (MLR) algorithms are used to make predictions about air quality, and MSE (Mean Squared Error), RMSE (Root Mean Square Error), MAE (Mean Squared error), and R² are used to determine how accurate the predictions are.     

The coupling of sand with ZVI/oxidants achieved proportional and highly efficient removal of arsenic

• Simply doping sands with ZVI achieved an even activation of ZVI by oxidants. • Sand doping facilitated proportional As trapping along the ZVI/oxidants column. • ZVI/sand/oxidants are highly efficient for arsenic removal. • ZVI/sand/oxidants reduced significantly the Fe²⁺ leaching and effluent turbidity. • More than 54% of arsenic was reduced to As(III) in ZVI/sand/oxidants system. The coupling of zero-valent iron (ZVI) with common oxidants has recently achieved very rapid and highly efficient removal of Heavy metals from wastewater. However, the uniform activation of ZVI throughout the column and the proportional removal of target contaminants are urgently required for the prevention of premature filter clogging and the extension of the effective column operational time. In this study, we successfully achieved this objective by simply doping granular sand with ZVI at appropriate weight ratios. When pure ZVI packed column was spiked with oxidants, the majority of As trapping occurred between the column inlet and the first sampling point. In a packed column with a 1:20 mixture of ZVI and sand, the average As removal efficiency was 36 (1st), 13.1 (2nd), 18.5 (3rd), 19.2 (4th) and 5.9% (5th outlet). The overall arsenic removal performance of the composite filling system of ZVI/sand was equally as efficient as that of the previous pure ZVI-packed system. Moreover, the leaching of Fe was significantly reduced with an increased sand ratio, resulting in clearer water with less turbidity. The results of X-ray photoelectron spectroscopy (XPS) demonstrated that more than 54% of the arsenic was reduced to As(III). X-ray diffraction (XRD) and scanning electron microscopy (SEM) confirmed the extensive corrosion of the ZVI surface, which resulted in various species of iron oxyhydroxides responsible for the highly efficient sequester of arsenic through reduction, adsorption, and coprecipitation.     

Synthesis and Characterization of Novel Heat Stable and Processable Optically Active Poly(Amide–Imide) Nanostructures Bearing Hydroxyl Pendant Group in an Ionic Green Medium

Ionic liquids (IL)s have been recognized as ‘green’ alternatives to the organic solvents in a range of synthesis, catalysis and electrochemistry due to their unique chemical and physical properties. In this investigation, a series of organosoluble, thermally stable and optically active hydroxyl-containing poly(amide–imide)s (PAI)s were prepared via polycondensation reaction of an aromatic diamine, 3,5-diamino-N-(4-hydroxyphenyl)benzamide (4), and different chiral amino acid-based diacids (3a–3e) in the presence of molten tetrabutylammonium bromide as a molten IL and triphenyl phosphite under classical heating method. This process is safe and green since toxic and volatile organic solvents such as N-methylpyrrolidone (NMP) and N,N′-dimethylacetamide (DMAc) were eliminated. The resulting new polymers were obtained in good yields with inherent viscosities ranging between 0.23 and 0.54 dL g^?1 and were characterized by Fourier transform infrared spectroscopy, specific rotation, powder X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), thermogravimetric analysis, elemental analysis, and in some cases by ¹H-NMR techniques. The FE-SEM micrographs and XRD showed that the synthesized PAIs were nanostructured and amorphous polymers. The effect of ultrasonic irradiation on the size of polymer particles was also investigated and the results showed that the size of polymer nanoparticles after ultrasonication became smaller than the size of them, before ultrasonic radiation. All of the polymers were readily soluble in many organic solvents such as N,N′-dimethyl sulfoxide, DMAc and NMP.     

Microbial contamination of drinking water in Pakistan—a review

Water pollution with pathogenic microorganisms is one of the serious threats to human health, particularly in developing countries. The main objective of this article is to highlight microbial contamination of drinking water, the major factors responsible for microbial contamination, and the resulting health problems in Pakistan. Furthermore, this study will be helpful for researchers and administrative agencies to initiate relevant studies and develop new policies to protect further deterioration of water supply with pathogenic microbes and ensure clean and safe drinking water to the public in Pakistan. In Pakistan, water at the source, in the distribution network, and at the consumer tap is heavily polluted with coliforms and fecal coliforms all over the country. An overview of more than 7,000 water samples reviewed here reveals that an average of over 71 and 58 % samples in the country was contaminated with total coliforms and fecal coliforms, respectively. Drinking water contamination accounts for 20 to 40 % of all diseases in the country, which causes national income losses of Rs 25–58 billion annually (US$0.25–0.58 billion, approximately 0.6–1.44 % of the country’s GDP). Improper disposal of industrial and municipal wastes is the most important factor responsible for water pollution in the country followed by cross-contamination due to old and leaking pipes and lack of water filtration and disinfection facilities. There is an urgent need for emergency steps to stop further deterioration of water quality and improve the existing water quality so as to protect the public from widespread waterborne diseases.     

Mobility of selected trace elements in Mediterranean red soil amended with phosphogypsum: experimental study

Soil amendment by phosphogypsum (PG) application becomes of increasing importance in agriculture. This may lead, however, to soil, plant, and groundwater contamination with trace elements (TEs) inherently present in PG. Monitoring of selected TEs (Pb, Zn, Cu, and Cd) distribution and mobility in a Mediterranean red soil profile has been performed in soil parcels applied with PG over a 16-month period. Concentrations were measured in soil and plant samples collected from various depth intervals at different points in time. TEs sequential extraction was performed on soil and PG samples. Results showed soil profile enrichment peaked 5 months after PG application for Cd, and 12 months for Pb, Zn, and Cu. Rainwater, pH, total organic carbon, and cationic exchange capacity were the main controlling factors in TEs accumulation in soils. Cd was transferred to a soil depth of about 20 cm. Zn exhibited mobility towards deeper layers. Pb and Cu were accumulated in around 20-55-cm-deep layers. PG increased the solubility of the studied TEs; PG-applied soils contained TEs bound to exchangeable and acid-soluble fractions in higher percentages than reference soil. Pb, Zn, and Cu were sorbed into mineral soil phases, while Cd was mainly found in the exchangeable (bio-available) form. The order of TEs decreasing mobility was Zn > Cd > Pb > Cu. Roots and leaves of existed plants, Cichorium intybus L., accumulated high concentrations of Cd (1-2.4 mg/kg), exceeding recommended tolerable levels, and thus signifying potential health threats through contaminated crops. It was therefore recommended that PG should be applied in carefully established, monitored, and controlled quantities to agricultural soils.     

Monitoring of trace amounts of heavy metals in different food and water samples by flame atomic absorption spectrophotometer after preconcentration by amine-functionalized graphene nanosheet

We are introducing graphene oxide modified with amine groups as a new solid phase for extraction of heavy metal ions including cadmium(II), copper(II), nickel(II), zinc(II), and lead(II). Effects of pH value, flow rates, type, concentration, and volume of the eluent, breakthrough volume, and the effect of potentially interfering ions were studied. Under optimized conditions, the extraction efficiency is >97 %, the limit of detections are 0.03, 0.05, 0.2, 0.1, and 1 μg L^?1 for the ions of cadmium, copper, nickel, zinc, and lead, respectively, and the adsorption capacities for these ions are 178, 142, 110, 125, and 210 mg g^?1. The amino-functionalized graphene oxide was characterized by thermogravimetric analysis, transmission electron microscopy, scanning electron microscopy, and Fourier transform infrared spectrometry. The proposed method was successfully applied in the analysis of environmental water and food samples. Good spiked recoveries over the range of 95.8–100.0 % were obtained. This work not only proposes a useful method for sample preconcentration but also reveals the great potential of modified graphene as an excellent sorbent material in analytical processes.     

Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study

Identifying areas that are susceptible to soil erosion is crucial for water resource planning and management efforts. Furthermore, modeling has proven helpful in recognizing and monitoring high-risk areas at the watershed scale. The Water Erosion Prediction Project (WEPP) geospatial interface (GeoWEPP) software integrates GIS with the WEPP to analyze the spatial variation in soil loss, and it has been used as a modeling tool to determine the areas that are most prone to soil erosion and to evaluate best management practices for the Kasilian watershed in Iran. As much as 62.4 % of the agronomic land in the Kasilian watershed is affected by a high magnitude of erosion (>5 t/ha). On the basis of this study, by using soybeans, high fertilization levels, and the drill-no-tillage system, reductions of erosion by almost 32.68–34.02 % are perceivable in three critical subwatersheds that are located in the cultivated lands. Also, it is projected that reductions in the production of sediment in the range of about 36.7–47.1 % are achievable by structural management within two critical, upland subwatersheds. So, by utilizing the best management strategies, sediment yield can be lowered and the conservation of soil and water is feasible at the watershed scale. These results objectively indicate that GeoWEPP can be efficaciously used for evaluating effective management practices for developing watershed conservation.     

Bat Diversity and Abundance as Indicators of Disturbance in Neotropical Rainforests

Abstract: Evaluating the degree of disturbance of any region to determine its relative importance for conservation purposes requires procedures that are relatively inexpensive and that yield accurate results fast. Because bats are abundant, diverse, and easy to sample, especially in the Neotropical rainforest, they fulfill several of the requirements of indicator species as identified in the literature. For 10 months we sampled bat communities in the Selva Lacandona in Chiapas, Mexico, at 15 sites representing five habitats. We also measured 10 variables representing vegetation structure and diversity at each site. With fuzzy-set techniques we produced a gradient classification of disturbance for the 15 sites based on the vegetation data. We explored the relationship between vegetation conditions, described as the membership degrees in the construct "fuzzy forest set" (the complementary fuzzy set of "disturbance"), and four bat community variables. Bat species richness, number of rare bat species, and the bat diversity index were positively correlated with the vegetation scores, and relative abundance of the most abundant bat species was negatively correlated with vegetation scores. A high number of phyllostomine species in a community is a good indicator of low levels of disturbance. Although a single indicator group will probably not be sufficient for decision-making processes in conservation, evaluating bat populations may be a good first step in assessing an area's conservation value, especially in rainforest regions.     

A stochastic conflict resolution model for trading pollutant discharge permits in river systems

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example of the Zarjub River in the northern part of Iran.