There is a sharp inclination to use green energy sources such as solar, hydro, and nuclear energy to accomplish the COP29 targets and sustainability goals. The current study attempts to explore the role of green solar, hydro, and agriculture land use apropos global pollutant emissions. In doing so, the study examines the impacts of agricultural land use, forest area, and urbanization on global emissions. The study uses the global historical data from 1990Q1 to 2021Q4. The authors employ the diagnostic tests, autoregressive distributed lag models, and causality analysis for empirical analysis. The autoregressive distributed lag model's results mentioned that agricultural land and forestry also help improve environmental sustainability and urban landscape in the short and long run. In addition, the results find linear and nonlinear impacts of green solar and nuclear energy to mitigate the global carbon emission levels. The structural change policies of industrialization and urbanization remain the critical obstacles to attaining environmental sustainability. The on-hand research contributes to the ongoing challenges faced by global economies regarding green energy sources, agriculture land management and their criticality in attaining a sustainable environment by reducing carbon emissions. The research recommends further investments in green solar, agriculture land management, and incentivizing clean energy sources to achieve sustainable global development.

The continuous rise in global environmental challenges has led to urgency toward establishing a secure framework to achieve sustainable development goals. This study establishes a novel theoretical framework to analyze the role of energy prices, energy consumption, gold prices and economic growth on environmental degradation in newly industrialized economies. To realize sustainable development goals and foster environmental defence, this study utilizes CS-ARDL as the main econometric approach to investigate the asymmetric association between environmental degradation and relevant factors. We also use AMG, CS-DL, Driscoll-Kray and FGLS to enhance the robustness of our findings. Our econometric approach reveals that energy resource prices and renewable energy consumption reduce environmental degradation, while gold prices and fossil energy consumption elevate environmental pollutants. We also confirm the existence of the EKC hypothesis. The findings of our extensive analysis paved the way for a well-designed environmental policy for NIC economies should focus on renewable energy consumption, green investments, and structural changes.

This research evaluates how energy (geothermal and coal), economic complexity, and technological innovation impact the ecological footprint in newly industrialized countries (NICs), considering the period 1990–2018. The authors employed economic complexity, technological innovation, and ecological footprint as significant considerations instead of standard environmental and economic parameters. The study used cross-sectional augmented distributed lag (CS-ARDL) and the pairwise Dumitrescu-Hurlin (DH) panel causality to consider the dynamic character of the correlation between the Environment and economic activities. The outcomes of the CS-ARDL showed that economic growth and coal energy intensify ecological footprint in both the long and short run. However, CS-ARDL results revealed that geothermal energy consumption, economic complexity, and technological innovation lessen the ecological footprint in NICs in the long and short run. Finally, the DH causality results revealed a unidirectional causality from geothermal, technological innovation, economic complexity, and coal energy use to ecological footprint. This demonstrates that all the exogenous variables have a predicted power on the ecological footprints in NICs. Based on these findings, policy measures to diversify products have the potential to tackle ecological problems.

The developed and emerging countries strive for sustainability and focus on enhancing greener energy and electric products. Adopting electric vehicles and utilizing green energy sources are essential to this objective. This study examines the synergy between EV technologies, green energy, and sustainability in China using quarterly data from 2010Q1 to 2022Q4. In addition, it considers the policy-level roles of economic complexity and research and development efforts in the EV industry. The authors employ novel time-series methods to assess long-term associations, including unit root testing, the Bayer-Hanck cointegration test, FMOLS, and DOLS. Robustness is checked using both a parametric method (least squares with breaks) and a non-parametric method (quantile regression). The empirical results reveal that electric vehicle technologies, economic complexity, and R&D expenditures exert an unfavorable effect on greenhouse gas emissions. By contrast, green energy and economic globalization significantly reduce ecological emissions in the long run. The robustness check analysis through parametric and non-parametric provides robust and valid outcomes. Promoting the adoption of electric vehicles and investing in green energy, and research & development intiaitves have significant policy implications for attaining environmental sustainability. lastly, enhancing economic complexity and fostering economic globalization should be considered to ensure a stable environment and facilitate sustainable development and better environmental quality.