Competitive role of nitrogen functionalities of N doped GO and sensitizing effect of Bi2O3 QDs on TiO2 for water remediation

The promising solar irradiated photocatalyst by pairing of bismuth oxide quantum dots (BQDs) doped TiO₂ with nitrogen doped graphene oxide (NGO) nanocomposite (NGO/BQDs-TiO₂) was fabricated. It was used for degradation of organic pollutants like 2,4-dichlorophenol (2,4-DCP) and stable dyes, i.e. Rhodamine B and Congo Red. X-ray diffraction (XRD) profile of NGO showed reduction in oxygenic functional groups and restoring of graphitic crystal structure. The characteristic diffraction peaks of TiO₂ and its composites showed crystalline anatase TiO₂. Morphological images represent spherical shaped TiO₂ evenly covered with BQDs spread on NGO sheet. The surface linkages of $\text{NO}?\mathrm{O}?\text{Ti}$, $\mathrm{C}?\mathrm{O}?\text{Ti}$, $\mathrm{B}\mathrm{i}?\mathrm{O}?\text{Ti}$ and vibrational modes are observed by Fourier transform infrared spectroscopy (FTIR) and Raman studies. BQDs and NGO modified TiO₂ results into red shifting in visible region as studied in diffused reflectance spectroscopy (DRS). NGO and BQDs in TiO₂ are linked with defect centers which reduced the recombination of free charge carriers by quenching of photoluminescence (PL) intensities. X-ray photoelectron spectroscopy (XPS) shows that no peak related to $\mathrm{C}?\mathrm{O}$ in NGO/BQDs-TiO₂ is observed. This indicated that doping of nitrogen into GO has reduced some oxygen functional groups. Nitrogen functionalities in NGO and photosensitizing effect of BQDs in ternary composite have improved photocatalytic activity against organic pollutants. Intermediate byproducts during photo degradation process of 2,4-DCP were studied through high performance liquid chromatography (HPLC). Study of radical scavengers indicated that ${\mathrm{O}}_2^{·?}$ has significant role for degradation of 2,4-DCP. Our investigations propose that fabricated nanohybrid architecture has potential for degradation of environmental pollutions.     

Classification of air quality using fuzzy synthetic multiplication

Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.     

Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO₂) into ozone (O₃) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O₃ in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O₃ concentration was tested. Results indicated that the presence of NO₂ and sunshine influence the concentration of O₃ in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.     

Health risk assessment of drinking arsenic-containing groundwater in Hasilpur,Pakistan: effect of sampling area,depth, and source

Environmental Science and Pollution Research - Currently, several news channels and research publications have highlighted the dilemma of arsenic (As)-contaminated groundwater in Pakistan. However,...     

Pesticide risk assessment: A study on inhalation and dermal exposure to 2,4-D and paraquat among Malaysian paddy farmers

A cross-section analytical study was conducted to evaluate the risk of pesticide exposure to those applying the Class II pesticides 2,4-D and paraquat in the paddy-growing areas of Kerian, Perak, Malaysia. It investigated the influence of weather on exposure as well as documented health problems commonly related to pesticide exposure. Potential inhalation and dermal exposure for 140 paddy farmers (handlers of pesticides) were assessed. Results showed that while temperature and humidity affected exposure, windspeed had the strongest impact on pesticide exposure via inhalation. However, the degree of exposure to both herbicides via inhalation was below the permissible exposure limits set by United States National Institute of Occupational Safety and Health (NIOSH). Dermal Exposure Assessment Method (DREAM) readings showed that dermal exposure with manual spraying ranged from moderate to high. With motorized sprayers, however, the level of dermal exposure ranged from low to moderate. Dermal exposure was significantly negatively correlated with the usage of protective clothing. Various types of deleterious health effects were detected among users of manual knapsack sprayers. Long-term spraying activities were positively correlated with increasing levels of the gamma-glutamyl transpeptidase (GGT) liver enzyme. The type of spraying equipment, usage of proper protective clothing and adherence to correct spraying practices were found to be the most important factors influencing the degree of pesticide exposure among those applying pesticides.     

Modeling of methane oxidation in landfill cover soil using an artificial neural network

Knowing the fraction of methane (CH₄) oxidized in landfill cover soils is an important step in estimating the total CH₄ emissions from any landfill. Predicting CH₄ oxidation in landfill cover soils is a difficult task because it is controlled by a number of biological and environmental factors. This study proposes an artificial neural network (ANN) approach using feedforward backpropagation to predict CH₄ oxidation in landfill cover soil in relation to air temperature, soil moisture content, oxygen (O₂) concentration at a depth of 10 cm in cover soil, and CH₄ concentration at the bottom of cover soil. The optimum ANN model giving the lowest mean square error (MSE) was configured from three layers, with 12 and 9 neurons at the first and the second hidden layers, respectively, log-sigmoid (logsig) transfer function at the hidden and output layers, and the Levenberg-Marquardt training algorithm. This study revealed that the ANN oxidation model can predict CH₄ oxidation with a MSE of 0.0082, a coefficient of determination (R ²) between the measured and predicted outputs of up to 0.937, and a model efficiency (E) of 0.8978. To conclude, further developments of the proposed ANN model are required to generalize and apply the model to other landfills with different cover soil properties.

Implications:

To date, no attempts have been made to predict the percent of CH₄ oxidation within landfill cover soils using an ANN. This paper presents modeling of CH₄ oxidation in landfill cover soil using ANN based on field measurements data under tropical climate conditions in Malaysia. The proposed ANN oxidation model can be used to predict the percentage of CH₄ oxidation from other landfills with similar climate conditions, cover soil texture, and other properties. The predicted value of CH₄ oxidation can be used in conjunction with the Intergovernmental Panel on Climate Change (IPCC) First Order Decay (FOD) model by landfill operators to accurately estimate total CH₄ emission and how much it contributes to global warming.     

Allelopathic potential of oil seed crops in production of crops: a review

Agricultural production enhancement has been realized by more consumption of fossil energy such as fertilizer and agrochemicals. However, the production provides the present human with sufficient and diversified commodities, but at the same time, deprives in some extent the resources from the future human as well. In the other hand, it is known that synthetic herbicides face worldwide threats to human’s health and environment as well. Therefore, it is a great challenge for agricultural sustainable development. The current review has been focussed on various oilseed crop species which launch efficient allelopathic intervention, either with weeds or other crops. Crop allelopathic properties can make one species more persistent to a native species. Therefore, these crops are potentially harmful to both naturalized as well as agricultural settings. On the other side, allelopathic crops provide strong potential for the development of cultivars that are more highly weed suppressive in managed settings. It is possible to utilize companion plants that have no deleterious effect on neighbor crops and can be included in intercropping system, thus, a mean of contributing to agricultural sustainable development. In mixed culture, replacement method, wherein differing densities of a neighbor species are planted, has been used to study phytotoxic/competitive effects. So, to use alternative ways for weed suppression has become very crucial. Allelochemicals have the ability to create eco-friendly products for weed management, which is beneficial for agricultural sustainable development. Our present study assessed the potential of four oilseed crops for allelopathy on other crops and associated weeds.     

Development of composting process of oil palm industrial wastes by multi-enzymatic fungal system

There is an increased interest in composting as an effective means of handling large amounts of organic wastes generated by oil palm industries in Malaysia. However, very few studies have been conducted to develop an effective composting process using the multi-enzymatic system. This study demonstrates an effective composting process of EFB (empty fruit bunch) with POME (palm oil mill effluent), using the optimized process parameters and compatible multi-enzymatic fungal system. A higher decrease (3 %) of organic matter was achieved in the fungal treated system, almost double that of the control (without inoculum). The lowest C/N ratio and soluble protein content recorded were about 17 and 128.82 g/kg, respectively. The maximum germination index obtained was 116 % at day 50 of treatment, which is considered high compared to the control (uninoculated). Furthermore, the maximum activity of ligninase enzyme was found to be 25.95 U/g and the highest cellulase activity was recorded at 0.975 U/g.     

Potential harmful elements in coal dust and human health risk assessment near the mining areas in Cherat,Pakistan

Environmental Science and Pollution Research - This study was aimed to investigate the potential harmful element (PHE) concentrations in coal dust and evaluate the human risk assessment and health...