Disposal of mine tailings can cause negative environmental effects by releasing contaminants to surface and underground water. Alkali activation is a promising technique for immobilizing metals in stabilization/solidification of these wastes. This study evaluates the leaching behavior of cemented bauxite tailings (BT) submitted to weathering conditions. The alkali-activated binder was composed of sugar cane bagasse ash, carbide lime, and sodium hydroxide solution. Comparisons of the durability and leaching behavior of BT stabilized with alkali-activated binder and high initial strength Portland cement were performed. The durability results for alkali-activated were similar to the Portland cement, showing an average difference of 16%. Portland cement showed favorable results in the encapsulation of heavy metals like Cd and Hg, while the alkali-activated cement on Al, Cr, and Se. For Ba, Fe, Mn, and Zn immobilization, both types of cement presented an equal performance. The durability and leaching behavior of stabilized bauxite tailings is governed by the cement content and porosity of the blends, as well as their pH.

The relationship between energy, environment, and economic growth has been received a lot of attention recently among scientific studies, but environmental sustainability remains a global issue. Renewable energy development, green technological innovations, and regulatory policy mechanisms can all help to reduce greenhouse gas emissions and support environmental sustainability. The purpose of this study was to look at the influence of renewable energy development, market regulation, and environment-related innovation on CO₂ emissions in the BRICS countries from 1990 to 2020. For empirical analysis, it uses second-generation panel unit root test and updated linear and nonlinear cointegration techniques. To this end, this study employs symmetric and asymmetric approach to linear and nonlinear relationship among study variables. The findings indicate that there is long-run symmetric and asymmetric relationship between renewable energy development, market regulation, environment-related innovation, and CO₂ emissions. The market regulation plays significant mediating role in relation between renewable energy development, environment-related innovation, and CO₂ emissions. Our findings suggest that BRICS countries need to more focus on the environment-related innovation and renewable energy development. They should design market-based environmental regulation policies, emphasize on environmental taxes, expand renewable energy development, and environment-related innovations. Such strategies are key to limiting CO₂ emissions and gain environmental sustainable.

This study evaluated the responses of a mixed culture of two cyanobacterial species (Microcystis aeruginosa and Synechocystis sp.) and two eukaryotic microalgal species (Raphidocelis subcapitata and Tetradesmus obliquus) to a mixture of three frequently detected antibiotics (tetracycline, ciprofloxacin and sulfamethoxazole) at environmentally relevant exposure doses of 60–300 ng/L. Mixed antibiotics selectively stimulated (p < 0.05) the growth and photosynthetic activity as well as generated transcriptomic responses in cyanobacteria without disrupting co-existing eukaryotic microalgae. Mixed antibiotics stimulated the growth of M. aeruginosa through the regulation of genes related to ribosome, photosynthesis, redox homeostasis, quorum sensing and nutrient metabolism. The proportion of M. aeruginosa among the four phytoplankton species in the mixed-culture system was increased from 33% to 38–44% under antibiotic exposure, which promoted the dominance of M. aeruginosa. Up-regulation of carbon catabolism-related genes contributed to the increased growth of Synechocystis sp. under antibiotic exposure. Since the antibiotic-stimulated growth rate of Synechocystis sp. was still lower than that of M. aeruginosa, the proportion of Synechocystis sp. in the mixed-culture system remained stable. Synechocystis sp. was less adaptive to antibiotic exposure than M. aeruginosa, due to a lower number of up-regulated ribosomal genes and photosynthesis-related genes. Antibiotic exposure reduced the proportions of two eukaryotic microalgal species in the mixed-culture system through a selective promotion of cyanobacterial competitiveness against eukaryotic microalgae, which may facilitate the formation of cyanobacteria bloom.

The work aims to synthesize and characterize vegetal charcoal (or biochar) from Syzygium cumini (AC-SC), evaluating the adsorption capacity for dexamethasone drug (DEX) removal, using the kinetic and equilibrium adsorption. The samples were characterized by N₂ porosimetry, X-ray diffraction, scanning electron microscopy with energy-dispersive spectroscopy, zeta potential, and zero charge point. Adsorption equilibrium was carried out applying the Langmuir, Freundlich, Redlich-Peterson, Sips, and Toth models, and kinetic adsorption applied the pseudo-first order, pseudo-second order, Elovich, Avrami, and Weber-Morris models. AC-SC showed a heterogeneous and porous surface, negatively charged, crystalline structure, specific surface area of the 2.14 m² g⁻¹ and pHZCP = 7.36. About the effect of the AC-SC concentration, 5.0 g L⁻¹ showed the best DEX removal (53.02%), about the others’ concentration (2.0 and 7.5 g L⁻¹). About the equilibrium and kinetic adsorption, the Sips model and pseudo-second order showed the best experimental data adjusted, indicating that the adsorption monolayer was dependent on the ions onto the biosorbent, with a maximum adsorption capacity of 0.744 mg g⁻¹ after 180 min. Therefore, AC-SC can be used as an alternative material in the removal of organic pollutants, such as drug removal.

Monitoring of groundwater is essential in the alluvial region of Tarn-Taran district, western Punjab, India where this freshwater source is being overexploited causing quality deterioration, groundwater depletion and posing serious threats to inhabitants. The present integrated study was conducted to appraise quality and suitability of groundwater for drinking/irrigation purposes, hydro-geochemical characteristics, source identification and associated health risks. In this study, 96% and 51% samples were detected with arsenic (As) and uranium (U), respectively higher than their acceptable limits posing high cancerous risks to local inhabitants via ingestion. Further, the quality indices revealed that groundwater of the study region is appropriate for irrigation but not suitable for drinking purposes. Hydro-geochemical studies showed that 83% of samples belonged to Ca²⁺–Mg²⁺–HCO₃⁻ type with major contribution of natural geogenic processes like rock-water interactions, silicate and carbonate dissolution along with reverse ion-exchange mechanisms in aquifer chemistry. Multivariate statistics revealed that along with geogenic sources, contribution of anthropogenic activities such as injudicious application of agrochemicals and domestic waste discharge was also very significant. Hazard quotient values for As were found to be 2.119 and 2.743 for children and adults, respectively representing both population groups prone to non-cancerous health risks due to As intake. Children were found to be more vulnerable than adults. This study draws an attention of public and local government about the current status of groundwater pollution in Tarn-Taran district, so that proper remediation steps can be taken to ensure the availability of good quality water.

The profitability of electric heating projects in Northern China is poor. A kind of combined market-oriented trading strategy to improve the economy of electric heating projects is put forward. The price game model for direct power purchase, compensation model for carbon emission reduction benefits and load aggregation revenue model are constructed, and the optimal proportion of clean energy and conventional energy consumed under the condition of ensuring heating reliability is analyzed. An electric heating project was analyzed as an example, the results showed that in the direct power purchase transaction, the power price is 0.2125 RMB/kWh, which is 0.0591 RMB/kWh lower than the catalogue tariff. Revenue from carbon trading and auxiliary service transaction is 469,913.87 RMB and 289,218.09 RMB, respectively, which is equivalent to reducing electricity cost of 0.0253 RMB/kWh and 0.0156 RMB/kWh, respectively. The ultimate power cost is 0.1716RMB/kWh, which is 0.1 RMB/kWh lower than the current catalogue tariff. Besides, the more clean energy an electric heating project consumes, the better its economy will be, and in this example, the best proportion of clean energy and conventional energy is 80% and 20%. The research results could help to promote the sustainable development of clean heating in northern China.

Bisphenol analogues (BPs) including bisphenol a (BPA) have been broadly utilized as industrial feedstocks and unavoidably discharged into water bodies. However, there is little published data on the occurrence, distribution, and environmental risks of other BPs in surface water. In this study, ten BPs besides BPA were analyzed in surface water from the Pearl River, South China. Among these detected BPs, BPA, bisphenol F (BPF), bisphenol AF (BPAF), and bisphenol S (BPS) were the most frequently detected compounds. The median concentrations of the measured BPs were ranked in the order of BPA (34.9 ng/L) > BPS (24.8 ng/L) > BPAF (10.1 ng/L) > bisphenol F (BPF) (9.0 ng/L) > bisphenol B (BPB) (7.6 ng/L) > bisphenol C (BPC) (1.2 ng/L). Among them, BPA and BPS were predominant BPs, contributing 68% of the total ten BPs in surface water of the Pearl River. These results demonstrated that BPA and BPS were the most extensively utilized and manufactured BPs in this region. The source analysis of BPs suggested that the BPs may be originated from domestic wastewater, wastewater treatment plant (WWTP) effluent, and the leaching of microplastic in surface water of the Pearl River. The calculated BP-derived estrogenic activity exhibited low to medium risks in surface water, but their combined estrogenic effects with other endocrine disrupting compounds should not be ignored.

Natural hazards and severe weather events are a matter of serious threat to humans, economic activities, and the environment. Flash floods are one of the extremely devastating natural events around the world. Consequently, the prediction and precise assessment of flash flood-prone areas are mandatory for any flood mitigation strategy. In this study, a new hybrid approach of machine learning (ML) algorithm and hydrologic indices opted to detect impacted and highly vulnerable areas. The obtained models were trained and validated using a total of 189 locations from Wadi Ghoweiba and surrounding area (case study). Various controlling factors including varied datasets such as stream transport index (STI), stream power index (SPI), lithological units, topographic wetness index (TWI), slope angle, stream density (SD), curvature, and slope aspect (SA) were utilized via hyper-parameter optimization setting to enhance the performance of the proposed model prediction. The hybrid machine learning (HML) model, developed by combining naïve Bayes (NïB) approach and hydrologic indices, was successfully implemented and utilized to investigate flash flood risk, sediment accumulation, and erosion predictions in the studied site. The synthesized new hybrid model demonstrated a model accuracy of 90.8% compared to 87.7% of NïB model, confirming the superior performance of the obtained model. Furthermore, the proposed model can be successfully employed in large-scale prediction applications.

Many countries are trying to achieve carbon neutrality targets by using environment-friendly technology and green growth. Thus, this analysis effort to identify the key role of green growth in improving the environmental quality. This study investigates the impact of green growth, income, environmental taxes, environment-friendly technology, renewable energy, and financial development in the context of 12 Asian economies over the period of 1990 to 2018. This study used the method of cross-section – augmented autoregressive distributed lag (CS–ARDL) to find out the impact of green growth and growth (GDP) on environment quality with some plausible variables under the scheme of environmental Kuznets curve (EKC). The study employed the method of CS–ARDL and for robustness the augmented mean group (AMG) method to find out the impact of green growth and GDP growth on environment quality with some plausible variables under the scheme of EKC. The results of CS–ARDL concluded that CO₂ is significantly affected by GDP growth, green growth, and technological change in the context of Asian economies. The GDP square is inversely and the GDP growth is positively related to the CO₂, indicating the presence of inverted U-shaped EKC in this region. But the inverse relationship between green growth and green growth square and concave EKC is observed in Asian countries. The study used the Dumitrescu and Hurlin panel test to gauge the causality between the variables. This study suggested that policymakers should focus on transforming the country’s energy system in ways that will reduce energy-related CO₂ emissions faster than previously expected.

The primary focus of this study is to evaluate the impact of various levels of education on CO2 emissions in China. Moreover, the study also tested the EKC hypothesis for different levels of education and economic development. The analysis employed disaggregate and aggregate data for education that included enrollment at primary, secondary, and tertiary levels and the average year of schooling. For empirical analysis, we employed an error correction model and bounds testing approach to cointegration. The results of the study provided some useful information both in the short and long run. All the proxies of education positively impact CO2 emissions at the initial level both in the short and long run; however, when we take the square of these variables, the effects of education on CO2 emissions become negative. Similarly, the impact of economic growth on CO2 emissions is positive in the short and long run, and the square of economic growth on CO2 emissions is negative, supporting the EKC hypothesis. China should increase investment in human capital that promotes green growth and environmental quality.