Unveiling the impact of aging on environmental sustainability in China: New insights from the Fourier ARDL approach

China is facing the dual challenges of rapid population aging and increasing environmental stress. Coordinating the relationship between demographic changes and environmental protection is a critical issue for China's sustainable development. Previous studies have primarily focused on carbon emissions or single pollutant indicators, overlooking the multidimensional nature of environmental stress and failing to fully consider the nonlinear relationships among variables. This study employs a more comprehensive load capacity factor (LCF) indicator and constructs a Fourier autoregressive distributed lag (Fourier ARDL) model, innovatively incorporating both nonlinear and periodic factors into the analysis. For the first time, this research systematically explores the nonlinear and cyclical interactions between population aging, economic growth, green technological innovation, and human capital, and their impacts on China's environmental sustainability. The results indicate that: (1) population aging, and economic growth exacerbate environmental stress, leading to a significant increase in LCF; (2) green technological innovation effectively alleviates environmental stress, having a significant negative impact on LCF; and (3) human capital has a dual effect on environmental sustainability, with a negative impact in the short term but a positive impact in the long term. Robustness checks further confirm these findings. This study suggests that China should proactively address population aging challenges, foster investment in green technological innovation, and prioritize the long-term accumulation of human capital to achieve sustainable development goals. [Display omitted] •Aging populations hinder ecological sustainability.•Human capital contributes to improved environmental quality but is detrimental in the short term.•Economic growth inhibits environmental quality.•Incorporating Fourier terms in the ARDL model captures periodic fluctuations.