Considering the need for environmental sustainability while ensuring economic growth and development by 2030, this study uses data on 123 developed and developing countries to examine factors that influence green growth. The empirical results show that economic development positively influences green growth. However, trade openness is detrimental to green growth. Regarding energy-related factors, we find energy consumption negatively affecting green growth, but renewable energy consumption significantly improves green growth. In further analysis, we find that the influence of these factors differs between developed and developing countries. The result implies that countries at a different development level will require different strategies in achieving the Sustainable Development Goals in 2030. The results are robust to alternative identification strategies such as the System Generalised Method of Movement, which accounts for potential endogeneity.

An automatic calibration framework of water quality parameters for surface runoff during modeling with InfoWorks ICM was constructed. The framework is based on a genetic algorithm (GA) and fully considers the calibration sequence for multiple water pollutants, namely, total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorous (TP). Meanwhile, four different objective functions including the Nash–Sutcliff efficiency coefficient (NSE), coefficient of determination (R²), percentage error in the peak (PEP), and percentage bias (PBIAS) were selected as fitness evaluators for the GA. The framework was applied successfully to a specific area of Fuzhou in China, and the multi-objective results were compared with the single-objective results. The comprehensive indexes of TSS, COD, TN, and TP by multi-objective calibration were lower than that of the single-objective calibration in both scenarios. Compared with single-objective calibration, the iterations to reach the optimal value were shortened 9, 5, 13, and 15 iterations by multi-objective calibration. Therefore, the findings showed that the multi-objective function GA was more balanced and more efficient than the single-objective function GA. Then, the uncertainty of the model was evaluated by using the samples generated by automatic calibration, which provided a reliable basis for the subsequent application of the model. This framework can be applied to other programs through adjustments of the number and weight of objective functions according to the specific situation, which will make the modeling more efficient and accurate.

The number of sunspots shows the solar activity level. During the high solar activity, emissions of matter and electromagnetic fields from the Sun make it difficult for cosmic rays to penetrate the Earth. When solar energy is high, cosmic ray intensity is lower, so that the solar magnetic field and solar winds affect the Earth externally and originate new viruses. In this paper, we assess the possible effects of sunspot numbers on the world virus appearance. The literature has no sufficient results about these phenomena. Therefore, we try to relate solar ray extremum to virus generation and the history of pandemics. First, wavelet decomposition is used for smoothing the sunspot cycle to predict past pandemics and forecast the future time of possible virus generation. Finally, we investigate the geographical appearance of the virus in the world to show vulnerable places in the world. The result of the analysis of pandemics that occurred from 1750 to 2020 shows that world’s great viral pandemics like COVID-19 coincide with the relative extrema of sunspot number. Based on our result, 27 pandemic (from 36) incidences are on sunspot extrema. Then, we forecast future pandemics in the world for about 110 years or 10 cycles using presented multi-step autoregression (MSAR). To confirm these phenomena and the generation of new viruses because of solar activity, researchers should carry out experimental studies.

This study deals with the development of alumina-supported cobalt (Co/Al₂O₃) catalysts with remarkable performance in dry reforming of methane (DRM) and least carbon deposition. The influence of Co content, calcination, and reduction temperatures on the physicochemical attributes and catalyst activity of the developed catalysts was extensively studied. For this purpose, several characterization techniques including ICP-MS, H₂ pulse chemisorption, HRTEM, H₂-TPR, N₂ adsorption desorption, and TGA were implemented, and the properties of the developed catalysts were carefully analyzed. The impact of reaction temperature, feed gas ratio, and gas hourly space velocity (GHSV) on the reactants conversion and products yield was investigated. Use of 10%Co/Al₂O₃ catalyst, calcined at 500°C and reduced under H₂ at 900°C in DRM reaction at 850°C, CH₄/CO₂ ratio of 1:1, and GHSV of 6 L.g⁻¹.h⁻¹ resulted in a remarkable catalytic activity and sustainable performance in long-term operation where great CO₂ (96%) and CH₄ (98%) conversions and high H₂ (83%) and CO (91%) yields with a negligible carbon deposition (3 wt%) were attained in 100-h on-stream reaction. The good performance of the developed catalyst in DRM reaction was attributed to the small Co particle size with well-dispersion on the alumina support which increased the catalytic activity and also the strong metal-support interaction which inhibited any serious metal sintering and enhanced the catalyst stability.

Existing PM₂.₅-morbidity studies using daily mean concentration as exposure metric may fail to capture intra-day variations of PM₂.₅ concentrations, resulting in underestimated health impacts to some extent. This study introduced a novel indicator, daily excessive concentration hours (DECH), defined as sums of per-hourly excessive concentrations of PM₂.₅ against a specific threshold within a day. PM₂.₅ DECHs were separately calculated as daily concentration-hours >8, 10, 15, 20, and 25 μg/m³ (abbreviations: DECH-8, DECH-10, DECH-15, DECH-20, and DECH-25). We adopted a time-stratified case-crossover design with conditional logistic regression models to compare risks of hospitalizations for chronic obstructive pulmonary disease (COPD) associated with PM₂.₅ mean and DECHs in Shenzhen, China. We observed highly comparable PM₂.₅-COPD associations using exposure metrics of daily mean and DECHs with above-defined thresholds. For instance, PM₂.₅ mean and DECHs showed similar increases in risks of COPD hospitalization for an interquartile range rise in exposure, with odds ratio estimates of 1.26 (95% confidence interval: 1.06–1.50) for PM₂.₅ mean, 1.24 (1.05–1.46) for DECH-10 and 1.21 (1.06–1.39) for DECH-25, respectively. Findings remained robust after further adjusting for gaseous pollutants (e.g., SO₂, NO₂, CO, and O₃) and meteorologic factors (e.g., wind speed and air pressure). Our study strengthened the evidence that DECHs could come be as a novel exposure metric in health risk assessments associated with short-term exposure to ambient PM₂.₅.

Antimicrobial resistance in the riverine ecosystem of urban areas is an alarming concern worldwide, indicating the importance of molecular monitoring to understand their patterning in urban and peri-urban areas. In the present study, we evaluated the influence of urban rivers on the connected peri-urban rivers of a riverine system of India in the context of antibiotic resistance genes. The rivers traversing through urban (Mula, Mutha, Pawana, and Ramnadi) and peri-urban stretches (Bhima and Indrayani) form the riverine system of Pune district in Maharashtra, India. The MinION-based shotgun metagenomic analysis revealed the resistome against 26 classes of antibiotics, including the last line of antibiotics. In total, we observed 278 ARG subtypes conferring resistance against multiple drugs (40%), bacitracin (10%), aminoglycoside (7.5%), tetracycline (7%), and glycopeptide (5%). Further, the alpha diversity analysis suggested relatively higher ARG diversity in the urban stretches than peri-urban stretches of the riverine system. The NMDS (non-metric multidimensional scaling) analysis revealed significant differences with overlapping similarities (stress value = 0.14, p-value = 0.004, ANOSIM statistic R: 0.2328). These similarities were reasoned by assessing the influence of downstream sites (sites at the outskirts of Pune city; however, directly impacted), which revealed significant differences in the ARG contents of urban and peri-urban stretches (stress value = 0.14, p-value = 0.001, ANOSIM statistic R: 0.6137). Overall, we detected the dissemination of antibiotic resistance genes from the polluted urban rivers into the peri-urban rivers located downstream in the connected riverine system potentially driven by anthropogenic activities.

The energy profile of India is dominated by fossil fuels, which create concerns over resource and environmental sustainability as fossil fuels are non-renewable and high carbon emitting. This scenario has necessitated the call for more renewables to replace fossil fuels to address resource and environmental sustainability concerns. This study, therefore, investigates the possibility of switching the fossil fuels of oil, coal, and natural gas for renewable energy in India. Using annual Indian data spanning more than four decades, a transcendental logarithmic production function based on a second-order Taylor Series approximation is estimated with the ridge regression technique. To achieve robustness, two equations with gross domestic product and adjusted net savings as regressands are estimated to proxy economic growth and sustainable development, respectively. The empirical results show substantial substitution possibilities between the fuels for both gross domestic product and adjusted net savings equations. The empirical findings show that India has the capacity to satisfy its energy needs through renewables to pursue not only economic growth but sustainable development. To actualize this potential, the Indian government should promote investment in renewables as this also promotes economic growth and development.

The adsorption of Cd by sand-attapulgite cutoff wall backfill media was investigated with batch experiments for different quantities of attapulgite in the mixture (30%, 40%, 60%, and 100%; dry weight). The adsorption capacity of the media for Cd increased with the increase of attapulgite content (Aₚ). The change of adsorbed amount (qₜ) with time (t) exhibited two-stage behavior, with more than 80% of the final qₜ attained in the first 30 min of the experiments. The Elovich equation was the most suitable for describing the adsorption kinetics of Cd by the sand-attapulgite media. The isotherm data were best fit by the Freundlich equation. Analysis of the results indicates that cation exchange was the major adsorption mechanism. The theoretical maximum adsorption capacities (qₘ) of the sand-attapulgite media for Cd calculated by the Langmuir isotherm model are 6311 mg/kg (Aₚ = 30%), 6437 mg/kg (Aₚ = 40%), 6534 mg/kg (Aₚ = 60%), and 7034 mg/kg (Aₚ = 100%). The removal percentage (RP) and the distribution coefficient (Kd) of Cd decreased with the increase of the initial Cd concentration (C₀) in the solution. An empirical equation for predicting Kd in terms of Aₚ and C₀ was developed: log(Kd) = − 1.22log(C₀) + 0.71Aₚ + 4.17 (r² = 0.924). This equation can be used to estimate the distribution coefficient of Cd for sand-attapulgite backfill media. This will provide valuable parameters for the study of Cd transport in the sand-attapulgite cutoff wall media, and for the design of such systems for management of landfill leachate.

Graphene-based nanomaterials (GBNs) have been widely used in various fields nowadays. However, they are reported to be highly toxic to some aquatic organisms. However, the multi-organ toxicity caused by pristine graphene (pG) and graphene oxide (GO) to the developing zebrafish (Danio rerio) larvae or juvenile and the underlying mechanisms is not fully known. Therefore, in the present study, the effect of pG and GO with environmental concentrations (0, 5, 10, 15, 20, and 25 μg/L of pG; 0, 0.1, 0.2, 0.3, and 0.4 mg/mL of GO) on multi-organ system in developing zebrafish larvae was experimentally assessed. The pG and GO were found to accumulate in the brain tissue that also caused significant changes in the heart beat and survival rate. The sizes of hepatocytes were reduced. Altered axonal integrity, affecting axon length and pattern in “Tg(mbp:eGFP) transgenic lines” was also observed. In addition, the results indicated pathological effects in major organs and with disrupted mitochondrial structure was quite obvious. The pG and GO bioaccumulation leads to multi organ toxicity in zebrafish larvae. In future, the existence of the current study can be extrapolated to other aquatic system in general and in particularly to humans.