The rapid development of industry has led to intensive energy and resource consumption, increasing carbon emissions. As key areas for carbon control, metropolitan regions play an essential role in China’s urbanization and regional development, yet research on predicting industrial carbon emissions remains insufficient. This study takes the Hangzhou Metropolitan Area in China as a case study and employs an extended STIRPAT model to predict industrial carbon emissions from 2024 to 2050 across different scenarios. The results show that industrial carbon emission intensity has the most significant impact on carbon emissions, followed by urbanization, population, economy, industrial structure, technology, energy intensity, and openness. The peak time of industrial carbon emissions varies significantly under different scenarios. The peak appears in 2026 under the deep emission reduction scenario, in 2028 under the green economy scenario, in 2030 under the baseline scenario, and does not occur by 2050 under the extensive development scenario. The green economy scenario achieves effective emission reductions with the least economic impact and is superior to the single-emission-reduction-oriented deep-emission-reduction scenario. This study responds to China’s “dual-carbon” strategy and provides a replicable and transferable regional pathway for industrial decarbonization and policy-making in other metropolitan areas.

Rapid urbanization has intensified ecosystem service supply–demand mismatches, severely constraining regional sustainable development. Ecological security patterns represent a critical strategy to address these challenges, yet existing studies predominantly focus on natural supply while neglecting human ecological demands. This study develops an integrated framework combining XGBoost machine learning and ecological network theory to assess and optimize ecological security patterns from a supply–demand perspective, using the Chengdu–Chongqing Urban Agglomeration in the upper Yangtze River Basin as a case study. Results reveal a distinct spatial pattern of “high supply in peripheries and high demand in urban cores”. Ecological demand sources and corridors have experienced explosive growth, expanding significantly faster than supply components. While the ecological supply–demand network has become more structurally complex with improved structural connectivity overall, the supply–demand balance has progressively deteriorated. Targeted optimization through supplementing key ecological sources and refining network structure enhanced connectivity by 136.46% and improved supply–demand balance by 35.4%. A “three zones, four corridors, six nodes” optimization scheme is proposed. This research provides valuable insights for mitigating ecological conflicts in rapidly urbanizing regions and informs evidence-based decision-making for territorial ecological restoration and public policy design to balance conservation and socioeconomic development.