The construction sector’s significant energy consumption poses a substantial challenge to achieving global “Carbon Peak and Carbon Neutrality” goals. This study addresses this challenge by proposing a sustainable design framework to optimize atrium spaces in commercial complexes within severe cold regions, where the conflict between high heating energy demands and the pursuit of high-quality spatial experiences is acute. Our climate-adaptive method integrates parametric modeling (Grasshopper) with building performance simulation (Ladybug Tools and Honeybee) to form a multi-objective optimization process using the NSGA-II algorithm. The goal is to simultaneously minimize operational energy (by reducing the seasonal solar heat gain difference, D-RAD) and enhance occupant well-being (by improving useful daylight illuminance, SUMUDI, and thermal discomfort, SUMPPD). Results demonstrate that our framework generated design solutions that significantly improve environmental performance compared to a baseline model: aggregate useful daylight illuminance (SUMUDI) increased by 90.2%, the solar heat gain difference (D-RAD) was reduced by 40.8%, and thermal discomfort (SUMPPD) decreased by 22.7%. This research provides a quantifiable and replicable methodology for sustainable architectural design, contributing directly to the measurement and monitoring of sustainability in the built environment by balancing energy conservation with human-centric design.

This study develops a spatial-analytical framework that integrates commercial hierarchy theory with cultural sustainability principles to support the sustainable development of traditional cultural marketplaces. Using kernel density estimation and Ripley’s K function analysis of 160 bazaars and 83,127 POI data points in Ürümqi, we established a hierarchical business district classification system incorporating both cultural-demographic factors and commercial indicators. Our findings reveal that culturally attuned spatial planning generates synergistic effects between heritage conservation and contemporary development needs. The research contributes to sustainable urban theory by extending Central Place Theory through cultural dimensions while providing practical design strategies validated through 15 case studies. This framework offers urban planners an implementable revitalization approach that maintains cultural authenticity while achieving a balance between commercial vitality and social cohesion, thereby presenting an effective pathway for sustainable urban development.

Nominally optimized atrium designs may lose reliability when geometric and envelope parameters deviate during implementation. Extending a previously established deterministic surrogate-assisted workflow, this study investigates uncertainty-aware design decision-making for a multi-atrium commercial building in Urumqi, China. The severe-cold climate is treated as a fixed environmental boundary condition, while uncertainty analysis is restricted to six implementation-related design variables. A Honeybee–EnergyPlus model supported by short-term field calibration was used to generate a Latin-hypercube dataset, and CatBoost surrogate models were developed for predicted percentage of dissatisfied (PPD), daylight autonomy at 300 lx (DA), and summer–winter solar-radiation difference (D-RAD). Sobol indices and SHAP were used to interpret parameter importance and interaction effects. Monte Carlo propagation of the six uncertain variables was embedded within NSGA-II using mean–variability robust objectives, and TOPSIS was applied to select representative solutions for subsequent space-syntax evaluation. The CatBoost models achieved global holdout test-set R² values of 0.990–0.994. Compared with the deterministic compromise solution, the robust solution shifted toward a different design configuration while maintaining broadly comparable mean performance. The uncertainty-adjusted DA and D-RAD objectives improved by approximately 2.21% and 6.20%, respectively, whereas the PPD objective deteriorated marginally by approximately 0.25%, reflecting the multi-objective trade-off inherent in the robust formulation. Expanded high-fidelity re-evaluation of ten Pareto-region designs revealed larger local errors for DA and D-RAD than suggested by the global holdout statistics, although the comparative performance ranking was strongly preserved. The results indicate that implementation-related design-variable uncertainty can alter the preferred design region and the balance among competing environmental objectives. Environmental robustness and spatial-configuration quality should therefore be treated as complementary criteria, with space-syntax analysis serving as a post-optimization screening tool rather than a direct measure of user experience.