Urban green infrastructure’s health impacts on aging populations remain understudied, particularly regarding gender-specific responses in cold-climate cities facing sustainability challenges. This study investigated how sustainable urban design supports healthy aging through a novel “static–dynamic” dual-temporal analysis framework. Through controlled field experiments with 345 elderly participants across three urban space types in Shenyang, China, we examined physiological indicators and psychological responses under winter conditions (4–8 °C), employing comprehensive environmental monitoring and health assessment protocols. Path analysis revealed that sustainable urban design influences health outcomes through both direct physiological pathways and indirect psychological mediation, with psychological states accounting for 56.3% of the total effect. Gender-specific analysis demonstrated that females exhibit higher environmental sensitivity (blood pressure variation coefficient: 0.171 vs. 0.079 for males) and stronger psychological mediation effects (β = −0.302 vs. β = −0.185 for males). The findings establish a theoretical foundation for implementing gender-responsive sustainable urban design strategies in cold-climate communities, demonstrating how green infrastructure can simultaneously address environmental sustainability and social equity goals while promoting healthy aging outcomes.

The flexible and precise design of photovoltaic (PV) skin morphologies for building facades constitutes a critical element for optimizing building energy efficiency and enhancing indoor spatial performance. However, the complex interrelationships among climatic parameters and their spatiotemporal variations pose significant challenges to the prior validity and accuracy of climate-adaptive parametric skin morphology adjustments. To address these limitations, this study proposes a morphological generative framework for climate-adaptive Building-Integrated Photovoltaics (BIPV) facades integrating Artificial Intelligence Algorithms and Bayesian prior-parameterized building envelopes. This framework is specifically designed to facilitate morphological decision-making regarding the overall climate-adaptive opening states of parametric PV skins under spatiotemporal dynamics. The proposed method integrates AI-based pattern recognition in spatiotemporal climate data with Bayesian Network-based prior probability techniques to derive optimal facade morphology schemes with the highest overall climate adaptability scores derived from weather forecasts, thereby achieving optimal transformations of the building envelope. Specifically, the model first employs an Artificial Intelligence Algorithm to generate the Bayesian Network structure required for overall climate adaptability scoring. Secondly, utilizing the Chinese Standard Weather Data (CSWD), the GRASSHOPPER algorithm is applied to implement variable parametric design on the facade skin, generating dynamic parametric skins and visual climatic data analysis cloud maps for energy benefit assessment. Finally, facade updates are executed based on the overall climate adaptability scores. The results demonstrate that the proposed framework effectively enables the real-time selection of optimal morphologies and opening states for dynamic skins based on comprehensive climatic adaptability criteria. Following model training and validation using 2025 Panjin meteorological data in the EnergyPlus Weather (EPW) format, the generated facade morphologies yielded solar radiation gains of 166.9 kWh/m²·month (peak month) for one of the optimal summer configurations and 90.5 kWh/m²·month (December) for one of the optimal winter configurations. Furthermore, by providing definitive evaluations of PV energy yields and indoor comfort levels across diverse weather scenarios, this framework offers explicit guidance for skin design, thereby reconciling the multi-objective optimization relationship between building energy conservation and occupant comfort.

Climate non-stationarity and intensifying extreme rainfall challenge flood-risk assessment in cold-region old industrial cities, where renewal must work within an established built fabric. Conventional assessments apply fixed indicator weights and thresholds derived from a single design event, although the factors controlling inundation and their response positions can shift with rainfall intensity. This study examines 208 urban green-space plots within Shenyang’s Third Ring Road, combining plot-level field sampling, GIS-based spatial indicators, and maximum inundation depths simulated for 1-, 3-, 10-, 30-, and 50-year return periods. Four analyses were applied along a common scenario axis: indicator screening defined the factor set; multi-group structural equation modeling characterized shifts in latent-variable paths; random forests with permutation importance ranked observed factors; partial dependence analysis located response breakpoints; and XGBoost-SHAP described sample-level contributions. All predictive results are reported from 30 repeated train–test splits with uncertainty intervals. Screening reduced 59 candidate indicators to 13 key factors. The diagnostic evidence indicates a mechanism-shift interval between the 10- and 30-year return periods: the structural path from spatial-pattern resistance to inundation becomes significant from the 10-year scenario, the total effect of surface-cover pressure first exceeds that of vertical storage capacity in the same scenario group, and the response breakpoint of impervious surface ratio tightens from about 58% to about 33% within this interval. Predictive importance is dominated by grey infrastructure density, green infrastructure density, and catchment radius in all scenarios. Renewal priorities therefore vary with rainfall intensity: internal storage and infiltration under regular rainfall, joint surface-cover and catchment control within the shift interval, and coordinated grey–green system responses under extreme scenarios. These findings are diagnostic and predictive, and retrofit benefits require experimental or quasi-experimental validation. The framework offers a methodological reference for further local calibration in comparable cold-region old industrial cities.

Cold-region community outdoor spaces are not only everyday activity settings for older adults in winter, but also public-space types that need to be translated into design evidence for architecture and healthy human-settlement research. Existing restorative-environment studies usually treat improved mood, perceived restoration, and environmental appraisal as evidence of health benefits. The key finding of this study is that subjective restoration and physiological recovery are not always synchronized after outdoor exposure in cold-region communities. This discordance reveals a design risk and an innovative value that can be overlooked when restoration is evaluated only through perception-based indicators. Based on a winter field exposure experiment with 345 older adults in a community in Shenyang, China, this study compared staged changes in systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), POMS, ROS, and ENPQ across an activity plaza, a greenway walkway, and a street corridor. It further developed a psychophysiological concordance classification and a residual cardiovascular risk indicator for the recovery period. The greenway walkway showed the most stable concordant recovery, with 86.84% of women and 79.35% of men showing concordant recovery. The activity plaza showed a clear pattern of emotional recovery: the proportions of women and men whose psychological state improved without a synchronized SBP decrease were 61.58% and 50.32%, respectively. The street corridor had the highest recovery-failure rates, at 92.63% for women and 91.61% for men. Among women, 90.53% reached SBP values of 140 mmHg or higher during the walking phase in the street corridor, and 59.47% remained above this risk threshold during recovery. These results show that health evaluation of cold-region community outdoor spaces should not rely only on subjective restoration indicators, but should also include psychophysiological concordance and residual risk after exposure. The study translates site health effects into three architectural design judgments: concordant-restoration spaces, emotional-restoration spaces, and recovery-failure spaces, providing a testable evidence framework for age-friendly community renewal, path organization, green buffering, and winter wind-protection design.