In this study, environmentally friendly activated biochar was produced from the wastes of the algal biodiesel industry (Gongolaria barbata (Stackhouse) Kuntze) using a microwave-assisted method. It was used as an adsorbent to remove hazardous aniline green dye from wastewater. The biochar, activated with phosphoric acid (BCH) was prepared in one step by a microwave-assisted method. Scanning electron microscopy (SEM), pHₚzc (pH at point of zero charges), Fourier transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET) techniques were used for the characterization of the adsorbent. The activated biochar presented a micropore volume of 0.181 cm³ g⁻¹ and SBET of 1089 m² g⁻¹. The effects of contact time, pH, and adsorbent amount on the adsorption were investigated. The optimal condition for the maximum adsorption of aniline green (AG) was found as pH (7.0), adsorbent amount (1 g L⁻¹), equilibrium time (40 min), and pollutant concentration (50 mg L⁻¹). The maximum removal percentage was proved to be 99.9% of AG removal. Analyses of experimental data were discussed using nonlinear model equations. The isotherm model can be well described by the Freundlich model. The pseudo-second-order model was suitable for the adsorption kinetics. The reusability ability of BCH for AG dye uptake was found to be 88.3% and 71.6%, for the 50 and 100 mg L⁻¹ pollutant concentrations, respectively, after the third cycle. Three cycles of adsorption and desorption showed that activated biochar is reusable. The economic analysis based on electricity consumption proved that the prepared adsorbent is suitable for large-scale use.

Rotating packed bed (RPB) is a promising technology which can be used to intensify mass transfer in absorption processes. A better understanding of fluid dynamics is crucial to fill the gap in fundamental knowledge. Raising awareness on new technology and creating rules for process design and control are also very important. The experimental investigation of fluid in rotating beds is a very complex and difficult issue. What is more, the knowledge of the phase behavior in an RPB device is still insufficient. Therefore, an CFD (computational fluid dynamics) simulation is proposed as a tool for the study of gas phase flow inside porous packing. This study presents a three-dimensional numerical model for two fluid models: k-ε and RNG k-ε, for predicting dry pressure drop. The obtained simulation outcome was compared with the experimental results. The experimental dry pressure drop for porous packing was investigated for rotational speed in the range from 150 rpm to 1500 rpm and compared to the results from the CFD model. The comparison between the experimental and simulation results indicates very good consistency for the entire range of the rotational speed of interest. CFD modelling is recognised as an adequate tool leading to the better understanding of gas phase behaviour inside an RPB, filling an essential gap in our knowledge of the hydrodynamics of rotating packing, which allows to improve the design and performance of the process in RPB in terms of minimizing energy and material consumption.

Selection of the most suitable biomass material for bio-fuel generation is a complex and multi-criteria decision problem as it engages many conflicting criteria which have to be assessed simultaneously. In the past, researchers have used subjective weighing techniques, which question the reliability of the approach. In this study, two objective weighing methods such as Criteria Importance Through Intercriteria Correlation (CRITIC) and Entropy are used to calculate the weights of evaluating criteria and Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS) is applied to select the suitable biomass material. This study considered six biomass alternatives such as lemongrass (A1), hard wood (A2), rice husk (A3), wheat straw (A4), rice straw (A5), and switch grass (A6), and seven important criteria such as volatile matter, fixed carbon, moisture and ash content, lignin, cellulose, and hemicellulose have been evaluated. Both the approaches show that switch grass has been the best alternative for yielding more bio-oil while rice straw is seen as the worst preferred option among the selected biomass materials. These approaches are systematic having simple computational procedure for determination of complete ranking of biomass materials. At the end of the study, the prediction is also validated by conducting pyrolysis experiments and characterization study. The experimental findings are identical and indicating a strong correlation between MCDM approach and real-time study.

Remote sensing and GIS technology were very helpful to determine an appropriate location of freshwater storage in Amhara, Ethiopia. The techniques were used to investigate the impact of lithology, surface geomorphology, slope parameters, drainage flow, drainage density, lineament density, land cover parameters on relief, and aerial and linear features and to understand their interrelationships. Morphometric parameters such as mean stream length (Lsm), stream length ratio (RL), bifurcation ratio (Rb), mean bifurcation ratio (Rbm), relief ratio (Rh), drainage density (Dd), stream frequency (Fs), drainage texture (Rt), form factor (Rf), circularity ratio (Rc), and elongation ratio (Re) were calculated. Spatial maps of morphometric parameters were produced by using AHP (analytical hierarchy process) of ArcGIS 10.3. Final priority map was generated by the overlay of those parameters with five categories of poor (16.6%), low (41.63%), moderate (29.61%), high (8.88%), and very high (3.28%) storage locations. The map showed that this study area belonged to the low to moderate storage location. The results exhibit precision-based assessment of the suitability for the dam construction sites of 6, 7, and 9 sub-basin zones. The outcome of this study strengthens the knowledge of geospatial analysis for water resources vulnerability and also allows policymakers in this drought-prone area to sustainably manage water supplies.

A three-compartment culture system was used to study the mechanism by which the AM fungus Funneliformis mosseae influences host plant growth and soil organic carbon (SOC) content in a northwest China coal mining area. A ¹³CO₂ pulse tracing technique was used to trace the allocation of maize photosynthetic C in shoots, roots, AM fungus, and soil. Carbon accumulation and allocation in mycorrhizal (inoculated with Funneliformis mosseae) and non-mycorrhizal treatments were detected. AM fungal inoculation significantly increased the ¹³C concentration and content in both above- and below-ground plant parts and also significantly enhanced anti-aging ability by increasing soluble sugars and catalase activity (CAT) in maize leaves while reducing foliar malondialdehyde content (MDA) and leaf temperature and promoted plant growth. AM fungi also increased P uptake to promote maize growth. Soil organic carbon (SOC), glomalin, microbial biomass carbon (MBC), and nitrogen (MBN) contents increased significantly after inoculation. A mutually beneficial system was established involving maize, the AM fungus and the microbiome, and the AM fungus became an important regulator of C flux between the above- and below-ground parts of the system. Inoculation with the AM fungus promoted plant growth, C fixation and allocation belowground to enhance soil quality. A positive above-belowground feedback appeared to be established.

In the last two decades, the tourism and energy sectors have grown rapidly and boosted economic growth, but it is inevitable that these sectors will cause environmental changes. So far, attempts have been made to determine the impact of the tourism and energy sectors on environmental degradation by examining pollution indicators such as CO₂ emissions and ecological footprint. However, these indicators neglect the supply side of the environment. In this context, this paper, for the first time, examines the influence of tourism, income, and energy consumption on the load capacity factor that results from dividing biocapacity by ecological footprint. Thus, the study aims to conduct a comprehensive sustainability analysis for Turkey by assessing the environmental quality on the supply and demand side. For this purpose, the study employs the novel dynamic Autoregressive-Distributed Lag (ARDL) simulations for the period 1965–2017, and the results indicate that tourist arrivals, energy consumption, and economic growth have a negative long run effect on the load capacity factor. Among these factors, only economic growth exerts a significant impact on the load capacity factor in both the short and long run. In the long run, the negative environmental effect of economic growth is less than in the short run. Therefore, the environmental Kuznets curve hypothesis is valid for Turkey. Based on the results, some policy recommendations are proposed to help Turkey improve its environmental quality.

Energy intensity reduction is an exigent issue for Iran, where energy consumption is so high. Therefore, finding effective policies to reduce energy intensity is essential. With this in mind, the impact of financial development, government investment, oil revenues, and trade openness on energy intensity is assessed in this study. We combined structural vector error correction model (SVECM) and directed acyclic graphs (DAG) technique to examine the relationships between study variables. The results of DAG prove that financial development, government investment, oil revenues, and trade openness influence the intensity of energy. Besides, the significant and long-run relationships among variables allowed us to apply SVECM. Impulse response functions and variance decomposition analysis indicate that government investment, oil revenues, and trade openness are negatively associated with the intensity of energy. Also, financial development positively influences energy intensity. Meanwhile, the impact of government investment is more significant than oil revenues, trade openness, and financial development impacts. So, government investment is the most effective policy regarding optimizing the consumption of energy and reducing energy intensity. We also advise policymakers to use oil revenues to increase government investment, enhance trade openness, and tax the private sector to improve the level of energy intensity.

The world is in a clash between the perspectives of economic expansion and sustainable environment. The high pace of technological progress opens space for fostering economic growth but at the same time, it creates a big dilemma for humans in protecting the environmental quality. The environmentally specific technologies are expected to help human beings to achieve dual objectives of economic prosperity and environmental sustainability. Despite its importance, attention to the role of environmental-related technologies in reducing environmental degradation is limited. This paper, therefore, intends to discover the impact of environmental-related technologies on the ecological footprint for 20 OECD from 1990 to 2015. The results endorse a long-run relationship between ecological footprint and green technologies, renewable energy, international trade, energy intensity, and real income. Environmental-related technologies and renewable energy consumption are found to be impetuous to sustainable development. The study provides relevant implications for policymakers to support the development and adoption of green technologies.

Macleaya cordata (Willd.) R. Br. are proposed for the application in phytoremediation of heavy metal-contaminated soil. In this paper, the physiological response, subcellular distribution, chemical form, ultrastructure, and manganese (Mn) absorption characteristics of M. cordata under the stress of 0, 3, 6, 9, 12, and 15 mmol/L manganese concentration were studied by sand culture experiment. The results showed that M. cordata seedlings show high tolerance to Mn stress with a concentration of less than 6 mmol/L, while higher Mn concentration showed a significant toxic effect. A low concentration of Mn (≤ 6 mmol/L) can promote the synthesis of chlorophyll and soluble protein; furthermore, superoxide dismutase and peroxidase activities responded positively. The accumulation of Mn in the inactive metabolic part (cell wall and vacuole) of M. cordata leaves might be one of the main Mn detoxification mechanism. According to the ultrastructure of M. cordata, high-concentration Mn²⁺ (≥ 12 mmol/L) stress can cause M. cordata cells to be distorted and deformed, black precipitates appeared in the intercellular space, mitochondria decrease, chloroplasts shrink, hungry particles increased, and starch granules decrease. The uptake ability of different tissues for Mn is leaf > root > stem, and transport coefficient decreases with the increase of Mn concentration. Clearly, M. cordata has a certain tolerance to manganese, which has the ecological application potential in Mn-polluted areas.

This work investigates the impacts of female employers, renewable energy, and education expenditures on CO2 emission in Pakistan, India, Bangladesh, and Sri Lanka. The annual data of 1990–2020 has been analyzed to present the empirical results. This work uses cross-sectional autoregressive distributed lag (CS-ARDL) approach to know long- and short-run coefficient values. The findings reveal that 1% increase in female employers, renewable energy, and education expenditures will decrease 0.04%, 0.64%, and 0.03% CO2 emissions, respectively, in the long run, which means female employers, renewable energy, and education spending are useful for South Asian countries to lower environmental pollution. This means that increasing female employers, ratio of renewable energy, and education expenditures are very important for South Asian countries to lower environmental pollution. This work recommends that education spending is providing environmental awareness, which is compulsory for cleaner environment.