A novel ZnO-CeO2-rGO (ZCG) ternary nanocomposite with varying ZnO/CeO2 weight proportions was synthesized by a hydrothermal process for photoelectrochemical water splitting and photocatalytic application. XRD diffraction peaks of ZCG nanocomposites displayed the patterns of ZnO and CeO2 nanoparticles, and SEM revealed irregular flake-like particles, which were uniformly decorated on the rGO matrix. Increase in the intensity ratio of D and G bands from Raman spectra revealed changes in oxygen bonding in the ZnO-rGO (ZG) and ZCG nanocomposites. The shift in the band edge positions and the decrease in the band gap with increase in the cerium oxide content in ZCG composites were observed from UV-Vis and Mott-Schottky plots. XPS results showed that Ce3+ fraction increased with an increase in the cerium oxide content in ZCG nanocomposites. The ZCG3 (8515) nanocomposite exhibited decreased electron-hole recombination rate as evidenced from the photoluminescence and electrochemical impedance spectroscopy Nyquist plots. The characteristic frequency in Bode’s plot shifted to a lower frequency for the ZCG3 electrode demonstrating low interfacial charge transfer resistance, and ZCG3 photoelectrode displayed a higher photocurrent density of 0.69 mA/cm2 at 1.5 V compared with other photoelectrode. The optimized and highly efficient ZCG3 nanocomposite exhibited improved photocatalytic degradation of methylene blue (MB) with a reaction rate constant of 0.0201 min-1. Combination of defects in the form of Ce3+ ion and surface oxygen vacancies coupled with rGO as the electron acceptor improved the charge carrier density and carrier transport in addition to the formation Schottky-type junction and the presence of an internal electric field.The removal of the harmful carcinogen arsenic from drinking water by a green technology is a major concern in the field of environmental engineering. The sorptive profile of arsenic remediation by calcined Mg-Fe-layered double hydroxide, fabricated by a one-pot synthesis technique, was investigated to delineate its applicability in real-life water. The physicochemical properties of adsorbent, as demonstrated from spectroscopy and microscopy, which described the existence of amorphous material with significant surface roughness possess selectivity towards arsenic. The isotherm and kinetic along with thermodynamic modeling exhibited the occurrence of spontaneous (ΔG0 value = - 8.084 kJ/mol to - 10.942 kJ/mol), endothermic (ΔH0 value = 12.135 kJ/mol), and physisorption reactions (Ead = 4.103-5.832 kJ/mol, Ea = 11.546 kJ/mol, S* = 0.0005  less then less then  1, and ΔHx = 9.23-16.29 kJ/mol) with high uptake rate and adsorption potential of adsorbent. The isotherm and kinetics were demonstrated by Temkin (R2 = 0.944-0.969) and Elovich (R2 = 0.996-0.998) models, respectively, with high statistical significance. The intraparticle diffusion model which established the rate-limiting step is the combination of both film and pore diffusions. The applicability of layered double hydroxide (LDH) material in the real-life water was confirmed by isotherm and kinetic modeling along with the regeneration/reuse potential. NIBR-LTSi The adsorptive removal of arsenic by the LDH material exhibited to be a promising technique without creating any secondary hazard.In addition to the adverse effect of extreme weather and weather variation across the globe, the ecological deficit accounting associated with the USA is perceived to have further worsen the country’s environmental quality. Considering the aforementioned motivation, this study examined the effects of cooling degree days, heating degree days and ecological footprint on environmental degradation in the USA over the period of 1960 to 2016. While employing the Autoregressive Distributed Lag (ARDL) and Bounds testing to cointegration approaches, the gross domestic product (GDP) per capita is further incorporated in the estimation model to avoid estimation bias thus enhancing a robust estimate. The result overwhelmingly found that the cooling degree days, the heating degree days and the ecological footprint accounting aggravates the country’s environmental degradation. Worse still, the study further presents that there is short-run adverse impacts of the heating and cooling degree days, and the short-run and long-run ecological footprint on the country’s environmental sustainability. Moreover, there is statistical evidence that the income growth in the USA especially in the long run will not also improve the environmental quality. Irrespective of the income-environmental degradation long-run relationship, the relieving impact of income growth on environmental degradation is observed in the short run. In general, the study presents relevant policy pathway for implementation.This study sets out to propose a new ensemble of probabilistic spatial modeling and multi-criteria decision-making comprised of stepwise areal constraining and Mahalanobis distance algorithms in order to assess areal suitability for landfilling. The Ardak watershed was selected as the study area due to encountering several cases of open garbage dumps and uncontrolled landfills which are one of the main sources of river water pollution in the upstream of the Ardak dam. The results revealed that the proposed algorithm successfully assists in inventory-irrespective probabilistic modeling of landfill siting which is mainly indebted to the role of areal constraining in providing training and validation samples for the Mahalanobis distance model. The latter also showed a robust pattern recognition results from which a discernible differentiation of the area was attained while the spatial dependencies between the environmental factors were taken into account. Mahalanobis distance also gave an outstanding performance in terms of goodness of fit (area under the success rate 89.367) and prediction power (area under the success rate 89.252). Based on a five-point scale classification scheme, about 2.7% and 2.6% of the study area, respectively, have high and very high suitability for landfilling, while the remaining area is shared between very low-to-moderate suitability classes. According to the current trail of literature regarding landfill site selection which mostly relies on mere areal filtering, a probabilistic model would give invaluable inferences regarding the pattern of suitability/susceptibility of the area of interest and causative role of the influential factors. Graphical Abstract.